About

Dr. Mohit Bansal is the John R. & Louise S. Parker Distinguished Professor and the Director of the MURGe-Lab (UNC-NLP Group) in the Computer Science department at the University of North Carolina (UNC) Chapel Hill. Prior to this, he was a research assistant professor (3-year endowed position) at TTI-Chicago. He received his Ph.D. in 2013 from the University of California at Berkeley (where he was advised by Dan Klein) and his B.Tech. from the Indian Institute of Technology at Kanpur in 2008. His research expertise is in natural language processing and multimodal machine learning, with a particular focus on multimodal generative models, grounded and embodied semantics, faithful language generation, and interpretable, efficient, and generalizable deep learning. He is a recipient of Presidential Early Career Award for Scientists and Engineers (PECASE), IIT Kanpur Young Alumnus Award, DARPA Director's Fellowship, NSF CAREER Award, Google Focused Research Award, Microsoft Investigator Fellowship, Army Young Investigator Award (YIP), DARPA Young Faculty Award (YFA), and outstanding paper awards at ACL, CVPR, EACL, COLING, and CoNLL. He has been a keynote speaker for the AACL 2023, CoNLL 2023, and INLG 2022 conferences. His service includes EMNLP and CoNLL Program Co-Chair, and ACL Executive Committee, ACM Doctoral Dissertation Award Committee, ACL Americas Sponsorship Co-Chair, and Associate/Action Editor for TACL, CL, IEEE/ACM TASLP, and CSL journals.

Work Experience

Computer Science department, UNC Chapel Hill (2016 — present) John R. & Louise S. Parker Distinguished Professorship Director, MURGe-Lab (UNC-NLP Group) Full Professor 2022-present Associate Professor: 2020-2022 Assistant Professor: 2016-2020
Toyota Technological Institute, Chicago (2013 — 2016) Research Assistant Professor
EECS, UC Berkeley (2008 — 2013) Graduate Student Researcher (Advisor: Dan Klein)
Google Research, Mountain View (Summer 2011) Research Intern (with John DeNero and Dekang Lin)
Microsoft Research, Redmond (Summer 2010) Research Intern (with Chris Quirk and Bob Moore)
Cornell University, Ithaca (Summer 2007) Research Intern (with Lillian Lee and Claire Cardie)

Selected Awards/Honors

Presidential Early Career Award for Scientists and Engineers (PECASE), 2025.

Provost's Kenan Senior Faculty Research and Scholarly Leave Award, 2023-2024.

IIT Kanpur Young Alumnus Award, 2023.

Keynote Speaker, CoNLL, 2023.

Keynote Speaker, AACL, 2023.

Keynote Speaker, INLG, 2022.

Early Career Award for Scientists and Engineers (ECASE), Army Research Office, 2021.

CoNLL Best Paper Runner-Up Award, 2021.

CVPR Best Student Paper Honorable Mention, 2021.

EACL Best Long Paper Award Honorable Mention, 2021.

UNC Phillip & Ruth Hettleman Prize for Artistic and Scholarly Achievement, 2020.

IJCAI Early Career Spotlight, 2020 (previous years: 2016, 2017, 2018, 2019)

John R. & Louise S. Parker Distinguished Professorship, 2020

DARPA Director's Fellowship, 2019

Microsoft Investigator Fellowship, 2019

Amazon Machine Learning Research Award, 2019

NSF-CAREER Award, 2019

Google Focused Research Award, 2019

ACL Best Short Paper Nomination, 2019

Salesforce Research Deep Learning Grant, 2018

Facebook Faculty Research Award, 2018

IBM Faculty Award, 2018

Army Research Office Young Investigator Award (ARO-YIP), 2018

COLING 'Area Chair Favorites' Paper Award, 2018

Adobe Faculty Research Award, 2018

Verisk AI Faculty Research Award, 2018

DARPA Young Faculty Award (DARPA-YFA), 2017

Facebook ParlAI Faculty Research Award, 2017

ACL Outstanding Paper Award, 2017

Google Faculty Research Award, 2016

Best Paper Award, ACL Representation Learning for NLP Workshop, 2016

Bloomberg Data Science Research Grant, 2016

NVidia Paper Award, NIPS Multimodal Machine Learning Workshop, 2015

Google Faculty Research Award, 2014

IBM Faculty Award, 2014

ACL Best Paper Award Honorable Mention, 2014

Best/Outstanding Reviewer Award, COLING 2018, NAACL 2018, NAACL 2015, EMNLP 2012

Outstanding Graduate Student Instructor Award, UC Berkeley, 2011

Tong Leong Lim Pre-Doctoral Prize, EECS, UC Berkeley, 2011

Qualcomm Innovation Fellowship, 2011

Student Fellowships/Awards:

Google PhD Fellowship, 2024 (David Wan)

Bloomberg PhD Fellowship, 2024 (David Wan) (declined)

Bloomberg PhD Fellowship, 2023 (Jaemin Cho)

CRA Outstanding Undergraduate Researcher Award Winner 2023 (Zineng Tang)

Google NLP PhD Fellowship, 2022 (Swarnadeep Saha)

Apple AI/ML PhD Fellowship, 2022 (Yichen Jiang)

Bloomberg PhD Fellowship, 2021 (Shiyue Zhang)

Google PhD Fellowship, 2021 (Peter Hase)

Adobe Research Fellowship, 2021 (Jie Lei)

Microsoft Research PhD Fellowship, 2019 (Ramakanth Pasunuru)

Facebook PhD Fellowship Finalist, 2019 (Ramakanth Pasunuru)

Bloomberg Data Science PhD Fellowship, 2019 (Hao Tan)

NSF Graduate Research Fellowship, 2018 (Lisa Bauer)

NSF Graduate Research Fellowship, 2019 (Darryl Hannan)

Royster Society Kenan Fellowship, 2019 (Peter Hase)

CRA Outstanding Undergraduate Researcher Award Runner-Up, 2020 (Sweta Karlekar)

CRA Outstanding Undergraduate Researcher Award Honorable Mention, 2019 (Han Guo)

CRA Outstanding Undergraduate Researcher Award Finalist, 2020 (Han Guo

Other Funding/Grants:

DARPA Environment-driven Conceptual Learning (ECOLE) (UNC PI)

ONR Science of Artificial Intelligence – Basic and Applied Research for the Naval Domain (Overall PI)

NSF-AI Institute on Engaged Learning (Core AI Lead; UNC PI)

NSF Future of Work at the Human-Technology Frontier (UNC Co-PI)

ONR Advancing Artificial Intelligence for the Naval Domain (UNC PI)

DARPA Machine Common Sense (MCS) (UNC PI)

DARPA Knowledge-directed Artificial Intelligence Reasoning Over Schemas (KAIROS) (UNC PI)

NSF-NIH SCH AURA Connecting Audio and Radio Sensing Systems to Improve Care at Home (UNC Co-PI)

Publications (+Code/Data)

• TOPIC-BASED LISTS:
  
  Multimodal (Images/Videos/Audio/Actions/Document Understanding+Generation, Any-to-Any Generation, Visual Programming, Long-Video, T2I/T2V Skill/Bias/Faithfulness Evaluation, Grounding, RoboNLP, Navigation/Assembling, Robotics Instructions, Story Visualization, etc.): Arxiv23a, Arxiv23b, Arxiv23c, Arxiv23d, Arxiv23e, NeurIPS23a, NeurIPS23b, NeurIPS23e, NeurIPS23g, NeurIPS23h, NeurIPS23i, EMNLPF23a, EMNLPF23b, ICCV23a, ICCV23b, ICCV23c, ACL23c, ACL23e, CVPR23a, CVPR23b, CVPR23c, CVPR23d, CVPR23e, WACV23a, EMNLP22a, EMNLP22d, NeurIPS22a, NeurIPS22b, NeurIPS22d, NeurIPS22f, ECCV22a, ECCV22b, COLING22b, NAACL22b, NAACLF22a, NAACLF22b, NAACLF22c, CVPR22a, CVPR22b, CVPR22W, ICLR22a, AAAI22a, AAAI22b, NeurIPS21a, NeurIPS21b, NeurIPS21d, EMNLP21g, EMNLP21c, ICML21a, ACL21d, NAACL21b, NAACL21c, NAACL21d, CVPR21a, AAAI21a, AAAI21c, EMNLP20b, EMNLP20d, EMNLPF20b, ECCV20, ACL20d, ACL20e, ACL20f, IJCAI20, AAAI20b, AAAI20d, ICRA20, EMNLP19a, ACL19d, ACL19e, NAACL19a, CVPR19, ICRA19, EMNLP18d, EMNLP18e, EMNLP18f, NAACL18a, NAACL18e, NAACL18f, CVPR18, AAAI18, WACV18, EMNLP17a, EMNLP17b, EMNLP17c, ACL17, CVPR17, HRI17, AAAI17a, EMNLP16b, EMNLP16c, CVPR16, AAAI16, CVPR14.
  
  Interpretability, Explainability, LLM/Agent Reasoning, CoT Evaluation, LLM Privacy/Safety, Model Editing, Model Beliefs, LLM Diagnosis/Faithfulness Evaluation, Adversarial Robustness, Debiasing, Data-Augmentation, Compositional Generalization, etc. : Arxiv23f, Arxiv23g, Arxiv23h, EMNLP23a, EMNLP23c, EMNLPF23b, NeurIPS23c , NeurIPS23f, ICCV23a, *SEM23a, ACL23a, ACLF23b, ACLF23c, IJCAI23a, ICLR23a, EACL23b, EACL23c, EMNLP22b, EMNLP22c, EMNLPF22a, TACL22a, ACL22b, ACL22c, NAACL22d, NeurIPS21c, EMNLP21a, EMNLP21d, EMNLP21f, EMNLP21j, NAACL21a, NAACL21e, NAACL21i, EACL21b, EMNLP20f, EMNLP20h, EMNLPF20a, EMNLPF20d, ACL20a, ACL20c, ACL20f, IJCAI20, AAAI20a, EMNLP19b, EMNLP19c, EMNLP19e, ACL19b, ACL19c, NAACL19a, AAAI19b, CoNLL18, NAACL18c, NAACL18d, EMNLP16a.
  
  Language Generation (Summarization, LLM Faithfulness/Factuality/Hallucinations, Dialogue, QG, Translation, Captioning, Robotic Instruction Generation, Explanation Generation, Code Generation, etc.): EMNLP23a, EMNLP23b, EMNLP23d, NeurIPS23c, ACL23a, ACL23d, ACLF23c, ICLR23a, EACL23a, EACL23b, EMNLP22c, AMTA22a, NAACL22a, NAACL22d, NAACL22f, NAACL22g, NAACL22h, NAACLF22d, NAACL22i, ACL22a, ACL22b, EMNLPF21a, EMNLP21i, CoNLL21a, ACL21b, ACL21c, ACL21e, ACLF21a, ACL21g, *SEM21a, NAACL21f, NAACL21g, NAACL21h, NAACL21l, AAAI21b, EMNLP20a, EMNLP20g, EMNLPF20a, ECCV20, ACL20e, AAAI20c, AAAI20d, EMNLP19e, ACL19d, ACL19f, NAACL19a, NAACL19c, EMNLP18a, EMNLP18c, EMNLP18d, EMNLP18f, CoNLL18, COLING18, TACL18, ACL18a, ACL18b, NAACL18b, NAACL18e, EMNLP17a, EMNLP17b, ACL17, CVPR17, HRI17, AAAI17b, NAACL16a.
  
  Efficiency: Parameter-Efficient Learning, Few-Shot Learning, Model Merging, Adapters, Side-Tuning, Continual+Transfer Learning, MoE, etc. : Arxiv23i, Arxiv23j, Arxiv23k, Arxiv23l, NeurIPS23d, EMNLPF23a, CVPR23e, ACL23f, ACLF23a, NeurIPS22c, NeurIPS22e, CVPR22b, EMNLP21e, EMNLP21h, ACL19a.
  
  QA: NeurIPS23g, ACL23b, EACL23f, AAAI22b, EMNLP20f, EMNLPF20d, ACL20d, ACL20f, AAAI20b, EMNLP19b, EMNLP19c, EMNLP19d, ACL19b, ACL19c, ACL19e, CVPR19, EMNLP18c, EMNLP18e, NAACL18d, EMNLP16c, EMNLP16d, ACL15.
  
  AutoML, Architecture Learning, Controllers, Bandits, MTL, RL, Calibration, etc.: Repl4NLP21, EMNLP20g, EMNLPF20d, EMNLPF20e, AAAI20a, EMNLP19e, ACL19a, NAACL19b, COLING18, TACL18, ACL18a, ACL18b, NAACL18b, EMNLP17a, ACL17, CVPR17.
  
  NLU+ Commonsense (NLI/Entailment/Next-Event Prediction, Fact Verification, Debiasing, Uncertainty, Distributive NLI, Representation Learning, Paraphrasing, Commonsense Reasoning, Knowledge Graphs, Parsing, Tagging, Relation Extraction, etc.): COLING22a, NAACL22c, NAACL22d, NAACL22e, NAACL22h, ACLF22a, EMNLP21b, EMNLP21c, ACL21f, ACLF21a, NAACL21a, NAACL21j, EACL21a, EACL21b, EACL23d, EMNLP20b, EMNLP20c, EMNLP20d, EMNLP20e, EMNLP20h, EMNLPF20c, ACL20b, ACL20c, ICRA20, EMNLP19d, AAAI19a, AAAI19b, EMNLP18c, EMNLP18f, NAACL18f, RepEval17, EMNLP17a, ACL17, ACL16, EMNLP16e, Repl4NLP16, NAACL16b, ICLR16, TACL15a, NAACL15, TACL15b, ACL14a, ACL14b.
  
  Social-NLP, Human Factors, Personality, Endangered Languages, etc.: ICCV23a, EACL23d, ACL22a, ACL21g, EMNLP20a, ACL20c, EMNLP18b, TACL18, WiNLP18, NAACL18c, NAACL18e, EMNLP16a, CVPR16.  
  
  
• RECENT PREPRINTS:
  

• DreamRunner: Fine-Grained Storytelling Video Generation with Retrieval-Augmented Motion Adaptation
  Zun Wang, Jialu Li, Han Lin, Jaehong Yoon, Mohit Bansal.
  arXiv Preprint: 2411.16657. [pdf/code]

• VideoRepair: Improving Text-to-Video Generation via Misalignment Evaluation and Localized Refinement
  Daeun Lee, Jaehong Yoon, Jaemin Cho, Mohit Bansal.
  arXiv Preprint: 2411.15115. [pdf/code]

• M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding
  Jaemin Cho, Debanjan Mahata, Ozan Irsoy, Yujie He, Mohit Bansal.
  arXiv Preprint: 2411.04952. [pdf/code]

• Self-Consistency Preference Optimization
  Archiki Prasad, Weizhe Yuan, Richard Yuanzhe Pang, Jing Xu, Maryam Fazel-Zarandi, Mohit Bansal, Sainbayar Sukhbaatar, Jason Weston, Jane Yu.
  arXiv Preprint: 2411.04109. [pdf/code]

• Reverse Thinking Makes LLMs Stronger Reasoners
  Justin Chih-Yao Chen, Zifeng Wang, Hamid Palangi, Rujun Han, Sayna Ebrahimi, Long Le, Vincent Perot, Swaroop Mishra, Mohit Bansal, Chen-Yu Lee, Tomas Pfister.
  arXiv Preprint: 2411.19865. [pdf/code]

• QAPyramid: Fine-grained Evaluation of Content Selection for Text Summarization
  Shiyue Zhang*, David Wan*, Arie Cattan, Ayal Klein, Ido Dagan, Mohit Bansal.
  arXiv Preprint: 2412.07096. [pdf/code]

• Bootstrapping Language-Guided Navigation Learning with Self-Refining Data Flywheel
  Zun Wang, Jialu Li, Yicong Hong, Songze Li, Kunchang Li, Shoubin Yu, Yi Wang, Yu Qiao, Yali Wang, Mohit Bansal, Limin Wang.
  arXiv Preprint: 2412.08467. [pdf/code]

• DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback
  Zaid Khan, Elias Stengel-Eskin, Jaemin Cho, Mohit Bansal.
  arXiv Preprint: 2410.23609. [pdf/code]

• Unbounded: A Generative Infinite Game of Character Life Simulation
  Jialu Li, Yuanzhen Li, Neal Wadhwa, Yael Pritch, David E. Jacobs, Michael Rubinstein, Mohit Bansal, Nataniel Ruiz.
  arXiv Preprint: 2410.18975. [pdf/code]

• Teaching Models to Balance Resisting and Accepting Persuasion
  Elias Stengel-Eskin, Peter Hase, Mohit Bansal.
  arXiv Preprint: 2410.14596. [pdf/code]

• On Positional Bias of Faithfulness for Long-form Summarization
  David Wan, Jesse Vig, Mohit Bansal, Shafiq Joty.
  arXiv Preprint: 2410.06215. [pdf/code]

• SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation
  Jaehong Yoon, Shoubin Yu, Vaidehi Patil, Huaxiu Yao, Mohit Bansal.
  arXiv Preprint: 2410.12761. [pdf/code]

• Adapt-∞: Scalable Lifelong Multimodal Instruction Tuning via Dynamic Data Selection
  Adyasha Maharana, Jaehong Yoon, Tianlong Chen, Mohit Bansal.
  arXiv Preprint: 2410.10636. [pdf/code]

• What Matters for Model Merging at Scale?
  Prateek Yadav, Tu Vu, Jonathan Lai, Alexandra Chronopoulou, Manaal Faruqui, Mohit Bansal, Tsendsuren Munkhdalai.
  arXiv Preprint: 2410.03617. [pdf/code]

• VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning
  Han Lin, Tushar Nagarajan, Nicolas Ballas, Mido Assran, Mojtaba Komeili, Mohit Bansal, Koustuv Sinha.
  arXiv Preprint: 2410.03478. [pdf/code]

• LASeR: Learning to Adaptively Select Reward Models with Multi-Armed Bandits
  Duy Nguyen*, Archiki Prasad*, Elias Stengel-Eskin, Mohit Bansal.
  arXiv Preprint: 2410.01735. [pdf/code]

• Glider: Global and Local Instruction-Driven Expert Router
  Pingzhi Li*, Prateek Yadav*, Jaehong Yoon, Jie Peng, Yi-Lin Sung, Mohit Bansal, Tianlong Chen.
  arXiv Preprint: 2410.07172. [pdf/code]

• Localizing Factual Inconsistencies in Attributable Text Generation
  Arie Cattan, Paul Roit, Shiyue Zhang, David Wan, Roee Aharoni, Idan Szpektor, Mohit Bansal, Ido Dagan.
  arXiv Preprint: 2410.07473. [pdf/code]

• MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning
  Justin Chih-Yao Chen, Archiki Prasad, Swarnadeep Saha, Elias Stengel-Eskin, Mohit Bansal.
  arXiv Preprint: 2409.12147. [pdf/code]

• AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric Knowledge
  Han Wang, Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal.
  arXiv Preprint: 2409.07394. [pdf/code]

• A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning
  Prateek Yadav*, Colin Raffel*, Mohammed Muqeeth, Lucas Caccia, Haokun Liu, Tianlong Chen, Mohit Bansal, Leshem Choshen, Alessandro Sordoni.
  arXiv Preprint: 2408.07057. [pdf/code]

• System-1.x: Learning to Balance Fast and Slow Planning with Language Models
  Swarnadeep Saha, Archiki Prasad, Justin Chih-Yao Chen, Peter Hase, Elias Stengel-Eskin, Mohit Bansal.
  arXiv Preprint: 2407.14414. [pdf/code]

• See It from My Perspective: Diagnosing the Western Cultural Bias of Large Vision-Language Models in Image Understanding
  Amith Ananthram, Elias Stengel-Eskin, Carl Vondrick, Mohit Bansal, Kathleen McKeown.
  arXiv Preprint: 2406.11665. [pdf/code]

• Are language models rational? The case of coherence norms and belief revision
  Thomas Hofweber, Peter Hase, Elias Stengel-Eskin, Mohit Bansal.
  arXiv Preprint: 2406.03442. [pdf/code]

• REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation via Asymptotic Entropy
  Haw-Shiuan Chang, Nanyun Peng, Mohit Bansal, Anil Ramakrishna, Tagyoung Chung.
  arXiv Preprint: 2406.07735. [pdf/code]

• VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos
  Ziyang Wang*, Shoubin Yu*, Elias Stengel-Eskin*, Jaehong Yoon, Feng Cheng, Gedas Bertasius, Mohit Bansal.
  arXiv Preprint: 2405.19209. [pdf/code]

• RACCooN: Remove, Add, and Change Video Content with Auto-Generated Narratives
  Jaehong Yoon*, Shoubin Yu*, Mohit Bansal.
  arXiv Preprint: 2405.18406. [pdf/code]

• Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion Model
  Han Lin*, Jaemin Cho*, Abhay Zala, Mohit Bansal.
  arXiv Preprint: 2404.09967. [pdf/code]

• DAM: Dynamic Adapter Merging for Continual Video QA Learning
  Feng Cheng*, Ziyang Wang*, Yi-Lin Sung, Yan-Bo Lin, Mohit Bansal, Gedas Bertasius.
  arXiv Preprint: 2403.08755. [pdf/code]

• CREMA: Multimodal Compositional Video Reasoning via Efficient Modular Adaptation and Fusion
  Shoubin Yu*, Jaehong Yoon*, Mohit Bansal.
  arXiv Preprint: 2402.05889. [pdf/code]

• Rethinking Machine Unlearning for Large Language Models
  Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu.
  arXiv Preprint: 2402.08787. [pdf/code]

• ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and Quantization
  Prateek Yadav, Leshem Choshen, Colin Raffel, Mohit Bansal.
  arXiv Preprint: 2311.13171. [pdf/code]

• LoopITR: Combining Dual and Cross Encoder Architectures for Image-Text Retrieval
  Jie Lei, Xinlei Chen, Ning Zhang, Mengjiao Wang, Mohit Bansal, Tamara Berg, Licheng Yu.
  arXiv Preprint: 2203.05465. [pdf][code]

• MLP Architectures for Vision-and-Language Modeling: An Empirical Study
  Yixin Nie*, Linjie Li*, Zhe Gan, Shuohang Wang, Chenguang Zhu, Michael Zeng, Zicheng Liu, Mohit Bansal, Lijuan Wang.
  arXiv Preprint: 2112.04453. [pdf][code]

• REFEREED PUBLICATIONS:
  
  2024

• LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language Models
  Elias Stengel-Eskin, Peter Hase, Mohit Bansal.
  Proceedings of NeurIPS 2024. [pdf/code]

• SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data
  Jialu Li*, Jaemin Cho*, Yi-Lin Sung, Jaehong Yoon, Mohit Bansal.
  Proceedings of NeurIPS 2024. [pdf/code]

• GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations
  Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, Kaidi Xu.
  Proceedings of NeurIPS 2024. [pdf/code]

• Fundamental Problems With Model Editing: How Should Rational Belief Revision Work in LLMs?
  Peter Hase, Thomas Hofweber, Xiang Zhou, Elias Stengel-Eskin, Mohit Bansal.
  Proceedings of TMLR 2024. [pdf/code]

• Unlearning Sensitive Information in Multimodal LLMs: Benchmark and Attack-Defense Evaluation
  Vaidehi Patil, Yi-Lin Sung, Peter Hase, Jie Peng, Tianlong Chen, Mohit Bansal.
  Proceedings of TMLR 2024. [pdf/code]

• Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models
  Yue Zhang, Ziqiao Ma, Jialu Li, Yanyuan Qiao, Zun Wang, Joyce Chai, Qi Wu, Mohit Bansal, Parisa Kordjamshidi.
  Proceedings of TMLR 2024. [pdf/code]

• FlexEControl: Flexible and Efficient Multimodal Control for Text-to-Image Generation
  Xuehai He, Jian Zheng, Jacob Zhiyuan Fang, Robinson Piramuthu, Mohit Bansal, Vicente Ordonez, Gunnar A Sigurdsson, Nanyun Peng, Xin Eric Wang.
  Proceedings of TMLR 2024. [pdf/code]

• A Simple LLM Framework for Long-Range Video Question-Answering
  Ce Zhang, Taixi Lu, Md Mohaiminul Islam, Ziyang Wang, Shoubin Yu, Mohit Bansal, Gedas Bertasius.
  Proceedings of EMNLP 2024. [pdf/code]

• Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM
  Haw-Shiuan Chang, Nanyun Peng, Mohit Bansal, Anil Ramakrishna, Tagyoung Chung.
  Proceedings of EMNLP 2024. [pdf/code]

• LLM Self-Correction with DeCRIM: Decompose, Critique, and Refine for Enhanced Following of Instructions with Multiple Constraints
  Thomas Palmeira Ferraz, Kartik Mehta, Yu-Hsiang Lin, Haw-Shiuan Chang, Shereen Oraby, Sijia Liu, Vivek Subramanian, Tagyoung Chung, Mohit Bansal, Nanyun Peng.
  Findings of EMNLP 2024. [pdf/code]

• Knowledge-Aware Reasoning over Multimodal Semi-structured Tables
  Suyash Vardhan Mathur, Jainit Sushil Bafna, Kunal Kartik, Harshita Khandelwal, Manish Shrivastava, Vivek Gupta, Mohit Bansal, Dan Roth.
  Findings of EMNLP 2024. [pdf/code]

• EnvGen: Generating and Adapting Environments via LLMs for Training Embodied Agents
  Abhay Zala*, Jaemin Cho*, Han Lin, Jaehong Yoon, Mohit Bansal.
  Proceedings of COLM 2024. [website]

• VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planning
  Han Lin, Abhay Zala, Jaemin Cho, Mohit Bansal.
  Proceedings of COLM 2024. [website]

• DiagrammerGPT: Generating Open-Domain, Open-Platform Diagrams via LLM Planning
  Abhay Zala, Han Lin, Jaemin Cho, Mohit Bansal.
  Proceedings of COLM 2024. [website]

• Contrastive Region Guidance: Improving Grounding in Vision-Language Models without Training
  David Wan, Jaemin Cho, Elias Stengel-Eskin, Mohit Bansal.
  Proceedings of ECCV 2024. [pdf/code]

• Diagnostic Benchmark and Iterative Inpainting for Layout-Guided Image Generation
  Jaemin Cho, Linjie Li, Zhengyuan Yang, Zhe Gan, Lijuan Wang, Mohit Bansal.
  Proceedings of CVPR Workshops 2024 (oral). [website]

• ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs
  Justin Chih-Yao Chen, Swarnadeep Saha, Mohit Bansal.
  Proceedings of ACL 2024. [pdf/code]

• Inducing Systematicity in Transformers by Attending to Structurally Quantized Embeddings
  Yichen Jiang, Xiang Zhou, Mohit Bansal.
  Proceedings of ACL 2024. [pdf/code]

• The Unreasonable Effectiveness of Easy Training Data for Hard Tasks
  Peter Hase, Mohit Bansal, Peter Clark, Sarah Wiegreffe.
  Proceedings of ACL 2024. [pdf/code]

• Evaluating Very Long-Term Conversational Memory of LLM Agents
  Adyasha Maharana, Dong-Ho Lee, Sergey Tulyakov, Mohit Bansal, Francesco Barbieri, Yuwei Fang.
  Proceedings of ACL 2024. [pdf/code]

• Soft Self-Consistency Improves Language Model Agents
  Han Wang*, Archiki Prasad*, Elias Stengel-Eskin*, Mohit Bansal.
  Proceedings of ACL 2024 (short). [pdf/code]

• RefineSumm: Self-Refining MLLM for Generating a Multimodal Summarization Dataset
  Vaidehi Patil, Leonardo F. R. Ribeiro, Mengwen Liu, Mohit Bansal, Markus Dreyer.
  Proceedings of ACL 2024. [pdf/code]

• Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences
  Xiyao Wang, Yuhang Zhou, Xiaoyu Liu, Hongjin Lu, Yuancheng Xu, Feihong He, Jaehong Yoon, Taixi Lu, Gedas Bertasius, Mohit Bansal, Huaxiu Yao, Furong Huang.
  Proceedings of ACL 2024. [pdf/code]

• ACUEval: Fine-grained Hallucination Evaluation and Correction for Abstractive Summarization
  David Wan, Koustuv Sinha, Srini Iyer, Asli Celikyilmaz, Mohit Bansal, Ramakanth Pasunuru.
  Findings of ACL 2024. [pdf/code]

• The Power of Summary-Source Alignments
  Ori Ernst, Ori Shapira, Aviv Slobodkin, Sharon Adar, Mohit Bansal, Jacob Goldberger, Ran Levy, Ido Dagan.
  Findings of ACL 2024. [pdf/code]

• MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
  Justin Chih-Yao Chen*, Swarnadeep Saha*, Elias Stengel-Eskin, Mohit Bansal.
  Proceedings of ICML 2024. [pdf/code]

• ReGAL: Refactoring Programs to Discover Generalizable Abstractions
  Elias Stengel-Eskin*, Archiki Prasad*, Mohit Bansal.
  Proceedings of ICML 2024. [pdf/code]

• Position Paper: TrustLLM: Trustworthiness in Large Language Models
  Lichao Sun, Yue Huang, Haoran Wang... Mohit Bansal, ....Yong Chen, Yue Zhao.
  Proceedings of ICML 2024. [pdf/code]

• CoDi-2: In-Context, Interleaved, and Interactive Any-to-Any Generation (spotlight)
  Zineng Tang, Ziyi Yang, Mahmoud Khademi, Yang Liu, Chenguang Zhu, Mohit Bansal.
  Proceedings of CVPR 2024. [pdf/code][website]

• Multimodal Representation Learning by Alternating Unimodal Adaptation
  Xiaohui Zhang, Jaehong Yoon, Mohit Bansal, Huaxiu Yao.
  Proceedings of CVPR 2024. [pdf/code]

• Rethinking Interactive Image Segmentation with Low Latency, High Quality, and Diverse Prompts
  Qin Liu, Jaemin Cho, Mohit Bansal, Marc Niethammer.
  Proceedings of CVPR 2024. [pdf/code]

• Branch-Solve-Merge Improves Large Language Model Evaluation and Generation
  Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, Mohit Bansal, Jason Weston, Xian Li.
  Proceedings of NAACL 2024. [pdf/code]

• ADaPT: As-Needed Decomposition and Planning with Language Models
  Archiki Prasad, Alexander Koller, Mareike Hartmann, Peter Clark, Ashish Sabharwal, Mohit Bansal, Tushar Khot.
  Findings of NAACL 2024. [pdf/code][website]

• Prompting Vision-Language Models For Aspect-Controlled Generation of Referring Expressions
  Danfeng Guo, Sanchit Agarwal, Arpit Gupta, Jiun-Yu Kao, Emre Barut, Tagyoung Chung, Jing Huang, Mohit Bansal.
  Findings of NAACL 2024. [pdf/code]

• Merging by Matching Models in Task Subspaces
  Derek Tam, Mohit Bansal, Colin Raffel.
  Proceedings of TMLR 2024. [pdf/code]

• Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
  Prateek Yadav, Peter Hase, Mohit Bansal.
  Proceedings of TMLR 2024. [pdf/code]

• Unified Embeddings for Multimodal Retrieval via Frozen LLMs
  Ziyang Wang, Heba Elfardy, Markus Dreyer, Kevin Small, Mohit Bansal.
  Findings of EACL 2024. [pdf/code]

• Hierarchical and Dynamic Prompt Compression for Efficient Zero-shot API Usage
  Yichen Jiang, Marco Vecchio, Mohit Bansal, Anders Johannsen.
  Findings of EACL 2024. [pdf/code]

• Exposing and Addressing Cross-Task Inconsistency in Unified Vision-Language Models
  Adyasha Maharana, Amita Kamath, Christopher Clark, Mohit Bansal, Aniruddha Kembhavi.
  Proceedings of TMLR 2024. [pdf/code]

• VLN-Video: Utilizing Driving Videos for Outdoor Vision-and-Language Navigation
  Jialu Li, Aishwarya Padmakumar, Gaurav Sukhatme, Mohit Bansal.
  Proceedings of AAAI 2024. [pdf/code]

• Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks (spotlight)
  Vaidehi Patil*, Peter Hase*, Mohit Bansal.
  Proceedings of ICLR 2024. [pdf/code]

• Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
  Jaemin Cho, Yushi Hu, Roopal Garg, Peter Anderson, Ranjay Krishna, Jason Baldridge, Mohit Bansal, Jordi Pont-Tuset, Su Wang.
  Proceedings of ICLR 2024. [pdf/code][website]

• Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy (spotlight)
  Pingzhi Li, Zhenyu Zhang, Prateek Yadav, Yi-Lin Sung, Yu Cheng, Mohit Bansal, Tianlong Chen.
  Proceedings of ICLR 2024. [pdf/code]

• Rephrase, Augment, Reason: Visual Grounding of Questions for Vision-Language Models
  Archiki Prasad, Elias Stengel-Eskin, Mohit Bansal.
  Proceedings of ICLR 2024. [pdf/code]

• D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning
  Adyasha Maharana, Prateek Yadav, Mohit Bansal.
  Proceedings of ICLR 2024. [pdf/code]

• ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models
  Yi-Lin Sung, Jaehong Yoon, Mohit Bansal.
  Proceedings of ICLR 2024. [pdf/code][website]

• Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
  Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao.
  Proceedings of ICLR 2024. [pdf/code]

  2023

• ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness
  Archiki Prasad, Swarnadeep Saha, Xiang Zhou, Mohit Bansal.
  Proceedings of EMNLP 2023. [pdf/code]

• HistAlign: Improving Context Dependency in Language Generation by Aligning with History
  David Wan, Shiyue Zhang, Mohit Bansal.
  Proceedings of EMNLP 2023. [pdf/code]

• Data Factors for Better Compositional Generalization
  Xiang Zhou, Yichen Jiang, Mohit Bansal.
  Proceedings of EMNLP 2023. [pdf/code]

• Generating Summaries with Controllable Readability Levels
  Leonardo F. R. Ribeiro, Mohit Bansal, Markus Dreyer.
  Proceedings of EMNLP 2023. [pdf/code]

• An Empirical Study of Multimodal Model Merging
  Yi-Lin Sung, Linjie Li, Kevin Lin, Zhe Gan, Mohit Bansal, Lijuan Wang.
  Findings of EMNLP 2023. [pdf/code]

• Debiasing Multimodal Models via Causal Information Minimization
  Vaidehi Patil, Adyasha Maharana, Mohit Bansal.
  Findings of EMNLP 2023. [pdf/code]

• Visual Programming for Text-to-Image Generation and Evaluation
  Jaemin Cho, Abhay Zala, Mohit Bansal.
  Proceedings of NeurIPS 2023. [pdf/code][website]

• CoDi: Any-to-Any Generation via Composable Diffusion
  Zineng Tang, Ziyi Yang, Chenguang Zhu, Michael Zeng, Mohit Bansal.
  Proceedings of NeurIPS 2023. [pdf/code][website]

• Can Language Models Teach Weaker Agents? Teacher Explanations Improve Students via Theory of Mind
  Swarnadeep Saha, Peter Hase, Mohit Bansal.
  Proceedings of NeurIPS 2023. [pdf/code]

• Resolving Interference When Merging Models
  Prateek Yadav, Derek Tam, Leshem Choshen, Colin Raffel, Mohit Bansal.
  Proceedings of NeurIPS 2023. [pdf/code]

• PanoGen: Text-Conditioned Panoramic Environment Generation for Vision-and-Language Navigation
  Jialu Li, Mohit Bansal.
  Proceedings of NeurIPS 2023. [pdf/code][website]

• Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge
  Editing in Language Models (spotlight)
  Peter Hase, Mohit Bansal, Been Kim, Asma Ghandeharioun.
  Proceedings of NeurIPS 2023. [pdf/code]

• Self-Chained Image-Language Model for Video Localization and Question Answering
  Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal.
  Proceedings of NeurIPS 2023. [pdf/code]

• Paxion: Patching Action Knowledge in Video-Language Foundation Models (spotlight)
  Zhenhailong Wang, Ansel Blume, Sha Li, Genglin Liu, Jaemin Cho, Zineng Tang, Mohit Bansal, Heng Ji.
  Proceedings of NeurIPS 2023. [pdf/code]

• Adaptive Contextual Perception: How to Generalize to New Backgrounds and Ambiguous Objects
  Zhuofan Ying, Peter Hase, Mohit Bansal.
  Proceedings of NeurIPS 2023. [pdf/code]

• DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers
  Jaemin Cho, Abhay Zala, Mohit Bansal.
  Proceedings of ICCV 2023. [pdf/code]

• Unified Coarse-to-Fine Alignment for Video-Text Retrieval
  Ziyang Wang, Yi-Lin Sung, Feng Cheng, Gedas Bertasius, Mohit Bansal.
  Proceedings of ICCV 2023. [pdf/code]

• Scaling Data Generation in Vision-and-Language Navigation (oral)
  Zun Wang, Jialu Li, Yicong Hong, Yi Wang, Qi Wu, Mohit Bansal, Stephen Gould, Hao Tan, Yu Qiao.
  Proceedings of ICCV 2023. [pdf/code]

• Extractive is not Faithful: An Investigation of Broad Unfaithfulness Problems in Extractive Summarization
  Shiyue Zhang*, David Wan*, Mohit Bansal.
  Proceedings of ACL 2023. [pdf/code]

• MeetingQA: Extractive Question-Answering on Meeting Transcripts
  Archiki Prasad, Trung Bui, Seunghyun Yoon, Hanieh Deilamsalehy, Franck Dernoncourt, Mohit Bansal.
  Proceedings of ACL 2023. [pdf/code]

• Revealing Single Frame Bias for Video-and-Language Learning
  Jie Lei, Tamara Berg, Mohit Bansal.
  Proceedings of ACL 2023. [pdf/code]

• MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies
  Shiyue Zhang, Shijie Wu, Ozan Irsoy, Steven Lu, Mohit Bansal, Mark Dredze, David Rosenberg.
  Proceedings of ACL 2023. [pdf/code]

• Non-Sequential Graph Script Induction via Multimedia Grounding
  Yu Zhou, Sha Li, Manling Li, Xudong Lin, Shih-Fu Chang, Mohit Bansal, Heng Ji.
  Proceedings of ACL 2023. [pdf/code]

• Exploring Continual Learning for Code Generation Models
  Prateek Yadav, Qing Sun, Hantian Ding, Xiaopeng Li, Dejiao Zhang, Ming Tan, Parminder Bhatia, Xiaofei Ma, Ramesh Nallapati, Murali Krishna Ramanathan, Mohit Bansal, Bing Xiang.
  Proceedings of ACL 2023 (short). [pdf/code]

• Exclusive Supermask Subnetwork Training for Continual Learning
  Prateek Yadav, Mohit Bansal.
  Findings of ACL 2023. [pdf/code]

• MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generation
  Swarnadeep Saha, Xinyan Velocity Yu, Mohit Bansal, Ramakanth Pasunuru, Asli Celikyilmaz.
  Findings of ACL 2023. [pdf/code]

• Evaluating the Factual Consistency of Large Language Models Through Summarization
  Derek Tam, Anisha Mascarenhas, Shiyue Zhang, Sarah Kwan, Mohit Bansal, Colin Raffel.
  Findings of ACL 2023. [pdf/code]

• Can Sequence-to-Sequence Transformers Naturally Understand Sequential Instructions?
  Xiang Zhou, Aditya Gupta, Shyam Upadhyay, Mohit Bansal, Manaal Faruqui.
  Proceedings of *SEM 2023. [pdf/code]

• On Conditional and Compositional Language Model Differentiable Prompting
  Jonathan Pilault, Can Liu, Mohit Bansal, Markus Dreyer.
  Proceedings of IJCAI 2023. [pdf/code]

• UDOP: Unifying Vision, Text, and Layout for Universal Document Processing (oral)
  Zineng Tang, Ziyi Yang, Guoxin Wang, Yuwei Fang, Yang Liu, Chenguang Zhu, Michael Zeng, Cha Zhang, Mohit Bansal.
  Proceedings of CVPR 2023. [pdf/code]

• Improving Vision-and-Language Navigation by Generating Future-View Image Semantics
  Jialu Li, Mohit Bansal.
  Proceedings of CVPR 2023. [pdf/code]

• Hierarchical Video-Moment Retrieval and Step-Captioning
  Abhay Zala*, Jaemin Cho*, Satwik Kottur, Xilun Chen, Barlas Oguz, Yashar Mehdad, Mohit Bansal.
  Proceedings of CVPR 2023. [pdf/code]

• VindLU: A Recipe for Effective Video-and-Language Pretraining
  Feng Cheng, Xizi Wang, Jie Lei, David Crandall, Mohit Bansal, Gedas Bertasius.
  Proceedings of CVPR 2023. [pdf/code]

• Vision Transformers are Parameter-Efficient Audio-Visual Learners
  Yan-Bo Lin, Yi-Lin Sung, Jie Lei, Mohit Bansal, Gedas Bertasius.
  Proceedings of CVPR 2023. [pdf/code]

• Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees
  Swarnadeep Saha, Shiyue Zhang, Peter Hase, Mohit Bansal.
  Proceedings of ICLR 2023. [pdf/code]

• Faithfulness-Aware Decoding Strategies for Abstractive Summarization
  David Wan, Mengwen Liu, Kathleen McKeown, Markus Dreyer and Mohit Bansal.
  Proceedings of EACL 2023. [pdf/code]

• GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models
  Archiki Prasad, Peter Hase, Xiang Zhou, Mohit Bansal.
  Proceedings of EACL 2023. [pdf/code]

• Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs
  Peter Hase, Mona Diab, Asli Celikyilmaz, Xian Li, Zornitsa Kozareva, Veselin Stoyanov, Mohit Bansal, Srinivasan Iyer.
  Proceedings of EACL 2023. [pdf/code]

• Social Commonsense for Explanation and Cultural Bias Discovery
  Lisa Bauer, Hanna Leth Tischer and Mohit Bansal.
  Proceedings of EACL 2023. [pdf/code]

• Enhancing Multi-Document Summarization with Cross-Document Graph-based Information Extraction
  Zixuan Zhang, Heba Elfardy, Markus Dreyer, Kevin Small, Heng Ji and Mohit Bansal.
  Proceedings of EACL 2023. [pdf/code]

• DeepMaven: Deep Question Answering on Long-Distance Movie/TV Show Videos with Multimedia Knowledge Extraction and Synthesis
  Yi Fung, Han Wang, Tong Wang, Ali Kebarighotbi, Prem Natarajan, Mohit Bansal, Heng Ji.
  Proceedings of EACL 2023. [pdf/code]

• Perceiver-VL: Efficient Vision-and-Language Modeling with Iterative Latent Attention
  Zineng Tang*, Jaemin Cho*, Jie Lei, Mohit Bansal.
  Proceedings of WACV 2023. [pdf/code]

  2022

• Evaluating and Improving Factuality in Multimodal Abstractive Summarization
  David Wan, Mohit Bansal.
  Proceedings of EMNLP 2022. [pdf/code]

• Mutual Exclusivity Training and Primitive Augmentation to Induce Compositionality
  Yichen Jiang*, Xiang Zhou*, Mohit Bansal.
  Proceedings of EMNLP 2022. [pdf/code]

• Are Hard Examples also Harder to Explain? A Study with Human and Model-Generated Explanations
  Swarnadeep Saha, Peter Hase, Nazneen Rajani, Mohit Bansal.
  Proceedings of EMNLP 2022 (short). [pdf/code]

• ALFRED-L: Investigating the Role of Language for Action Learning in Interactive Visual Environments
  Arjun Akula, Spandana Gella, Aishwarya Padmakumar, Mahdi Namazifar, Mohit Bansal, Jesse Thomason, Dilek Hakkani-Tur.
  Proceedings of EMNLP 2022 (short). [pdf/code]

• Analyzing the Limits of Self-Supervision in Handling Bias in Language
  Lisa Bauer, Karthik Gopalakrishnan, Spandana Gella, Yang Liu, Mohit Bansal, Dilek Hakkani-Tur.
  Findings of EMNLP 2022. [pdf/code]

• An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
  Jiaao Chen*, Derek Tam*, Colin Raffel, Mohit Bansal, Diyi Yang.
  Proceedings of TACL 2022. [pdf/code]

• TVLT: Textless Vision-Language Transformer (oral)
  Zineng Tang*, Jaemin Cho*, Yixin Nie*, Mohit Bansal.
  Proceedings of NeurIPS 2022. [pdf/code]

• VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives
  Zhuofan Ying*, Peter Hase*, Mohit Bansal.
  Proceedings of NeurIPS 2022. [pdf/code]

• LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer Learning
  Yi-Lin Sung, Jaemin Cho, Mohit Bansal.
  Proceedings of NeurIPS 2022. [pdf/code]

• VidIL: Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners
  Zhenhailong Wang, Manling Li, Ruochen Xu, Luowei Zhou, Jie Lei, Xudong Lin, Shuohang Wang, Ziyi Yang, Chenguang Zhu, Derek Hoiem, Shih-Fu Chang, Mohit Bansal, Heng Ji.
  Proceedings of NeurIPS 2022. [pdf/code]

• Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
  Haokun Liu*, Derek Tam*, Mohammed Muqeeth*, Jay Mohta, Tenghao Huang, Mohit Bansal, Colin Raffel.
  Proceedings of NeurIPS 2022. [pdf/code]

• WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models (oral)
  Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef, Yuval Elovici, Mohit Bansal, Gabriel Stanovsky, Roy Schwartz.
  Proceedings of NeurIPS 2022 (datasets/benchmarks track). [pdf/code]

• StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation
  Adyasha Maharana, Darryl Hannan, Mohit Bansal.
  Proceedings of ECCV 2022. [pdf/code]

• ECLIPSE: Efficient Long-range Video Retrieval using Sight and Sound (oral)
  Yan-Bo Lin, Jie Lei, Mohit Bansal, Gedas Bertasius.
  Proceedings of ECCV 2022. [pdf/code]

• GraDA: Graph Generative Data Augmentation for Commonsense Reasoning
  Adyasha Maharana, Mohit Bansal.
  Proceedings of COLING 2022. [pdf/code]

• GraVL-BERT: Graphical Visual-Linguistic Representations for Multimodal Coreference Resolution
  Danfeng Guo, Arpit Gupta, Sanchit Agarwal, Jiun-Yu Kao, Shuyang Gao, Arijit Biswas, Chien-Wei Lin, Tagyoung Chung, Mohit Bansal.
  Proceedings of COLING 2022. [pdf/code]

• How Robust is Neural Machine Translation to Language Imbalance in Multilingual Tokenizer Training?
  Shiyue Zhang, Vishrav Chaudhary, Naman Goyal, James Cross, Guillaume Wenzek, Mohit Bansal, Francisco Guzman.
  Proceedings of AMTA 2022. [pdf/code]

• FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization
  David Wan, Mohit Bansal.
  Proceedings of NAACL 2022. [pdf][code]

• CoSIm: Commonsense Reasoning for Counterfactual Scene Imagination
  Hyounghun Kim*, Abhay Zala*, Mohit Bansal.
  Proceedings of NAACL 2022. [pdf][code]

• Masked Part-Of-Speech Model: Does Modeling Long Context Help Unsupervised POS-tagging?
  Xiang Zhou, Shiyue Zhang, Mohit Bansal.
  Proceedings of NAACL 2022. [pdf][code]

• FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations
  Leonardo Ribeiro, Mengwen Liu, Iryna Gurevych, Markus Dreyer, Mohit Bansal.
  Proceedings of NAACL 2022. [pdf][code]

• On Curriculum Learning for Commonsense Reasoning
  Adyasha Maharana, Mohit Bansal.
  Proceedings of NAACL 2022 (short). [pdf][code]

• Proposition-Level Clustering for Multi-Document Summarization
  Ori Ernst, Avi Caciularu, Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Jacob Goldberger, Ido Dagan.
  Proceedings of NAACL 2022. [pdf][code]

• Interactive Query-Assisted Summarization via Deep Reinforcement Learning
  Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Ido Dagan, Yael Amsterdamer.
  Proceedings of NAACL 2022. [pdf][code]

• Enhanced Knowledge Selection for Grounded Dialogues via Document Semantic Graphs
  Sha Li, Mahdi Namazifar, Di Jin, Mohit Bansal, Heng Ji, Yang Liu, Dilek Hakkani-Tur.
  Proceedings of NAACL 2022. [pdf][code]

• CLEAR: Improving Vision-Language Navigation with Cross-Lingual, Environment-Agnostic Representations
  Jialu Li, Hao Tan, Mohit Bansal.
  Findings of NAACL 2022. [pdf][code]

• Fine-grained Image Captioning with CLIP Reward
  Jaemin Cho, Seunghyun Yoon, Ajinkya Kale, Franck Dernoncourt, Trung Bui, Mohit Bansal.
  Findings of NAACL 2022 (short). [pdf][code]

• Multimodal Intent Discovery from Livestream Videos
  Adyasha Maharana, Quan Hung Tran, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter W Chang, Mohit Bansal.
  Findings of NAACL 2022. [pdf][code]

• Efficient Few-Shot Fine-Tuning for Opinion Summarization
  Arthur Bražinskas, Ramesh Nallapati, Mohit Bansal, Markus Dreyer.
  Findings of NAACL 2022. [pdf][code]

• SETSum: Summarization and Visualization of Student Evaluations of Teaching
  Yinuo Hu*, Shiyue Zhang*, Viji Sathy, A. T. Panter, Mohit Bansal.
  Proceedings of NAACL 2022 (demo). [pdf][code]

• RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios
  Xinya Du, Zixuan Zhang, Sha Li, Pengfei Yu, Hongwei Wang, Tuan Lai, Xudong Lin, Ziqi Wang, Iris Liu, Ben Zhou, Haoyang Wen, Manling Li, Darryl Hannan, Jie Lei, Hyounghun Kim, Rotem Dror, Haoyu Wang, Michael Regan, Qi Zeng, Qing Lyu, Charles Yu, Carl Edwards, Xiaomeng Jin, Yizhu Jiao, Ghazaleh Kazeminejad, Zhenhailong Wang, Chris Callison-Burch, Mohit Bansal, Carl Vondrick, Jiawei Han, Dan Roth, Shih-Fu Chang, Martha Palmer, Heng Ji.
  Proceedings of NAACL 2022 (demo). [pdf][code]

• EnvEdit: Environment Editing for Vision-and-Language Navigation
  Jialu Li, Hao Tan, Mohit Bansal.
  Proceedings of CVPR 2022. [pdf][code]

• VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks
  Yi-Lin Sung, Jaemin Cho, Mohit Bansal.
  Proceedings of CVPR 2022. [pdf][code]

• VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning
  Hao Tan, Jie Lei, Thomas Wolf, Mohit Bansal.
  Proceedings of T4V Workshop, CVPR 2022. [pdf][code]

• How can NLP Help Revitalize Endangered Languages? A Case Study and Roadmap for the Cherokee Language
  Shiyue Zhang, Ben Frey, Mohit Bansal.
  Proceedings of ACL 2022. [pdf][code]

• Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning
  Swarnadeep Saha, Prateek Yadav, and Mohit Bansal.
  Proceedings of ACL 2022. [pdf][code]

• Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning
  Xiang Zhou*, Yixin Nie*, Mohit Bansal.
  Findings of ACL 2022. [pdf][code]

• When Can Models Learn From Explanations? A Formal Framework for Understanding the Roles of Explanation Data
  Peter Hase, Mohit Bansal.
  Proceedings of LNLS Workshop, ACL 2022. [pdf][bib][code]

• CLIP-ViL: How Much Can CLIP Benefit Vision-and-Language Tasks?
  Sheng Shen, Liunian Harold Li, Hao Tan, Mohit Bansal, Anna Rohrbach, Kai-Wei Chang, Zhewei Yao, Kurt Keutzer.
  Proceedings of ICLR 2022. [pdf][code]

• CAISE: Conversational Agent for Image Search and Editing
  Hyounghun Kim, Doo Soon Kim, Seunghyun Yoon, Franck Dernoncourt, Trung Bui, Mohit Bansal.
  Proceedings of AAAI 2022. [pdf][code]

• MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Grounding
  Revanth Gangi Reddy, Xilin Rui, Manling Li, Xudong Lin, Haoyang Wen, Jaemin Cho, Lifu Huang, Mohit Bansal, Avirup Sil, Shih-Fu Chang, Alexander Schwing, Heng Ji.
  Proceedings of AAAI 2022. [pdf][code]

• Scientific Chart Summarization: Datasets and Improved Text Modeling
  Hao Tan, Chen-Tse Tsai, Yujie He, Mohit Bansal.
  Proceedings of SDU Workshop, AAAI 2022. [pdf][code]

  2021

• VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer
  Zineng Tang, Jaemin Cho, Hao Tan, Mohit Bansal.
  Proceedings of NeurIPS 2021. [pdf][code]

• QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries
  Jie Lei, Tamara L. Berg, Mohit Bansal.
  Proceedings of NeurIPS 2021. [pdf][code]

• The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations
  Peter Hase, Harry Xie, Mohit Bansal.
  Proceedings of NeurIPS 2021. [pdf][code]

• VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
  Linjie Li*, Jie Lei*, Zhe Gan, Licheng Yu, Yen-Chun Chen, Rohit Pillai, Yu Cheng, Luowei Zhou, Xin Eric Wang, William Yang Wang, Tamara Lee Berg, Mohit Bansal, Jingjing Liu, Lijuan Wang, Zicheng Liu.
  Proceedings of NeurIPS 2021 (datasets/benchmarks track). [pdf][website]

• Finding a Balanced Degree of Automation for Summary Evaluation
  Shiyue Zhang, Mohit Bansal.
  Proceedings of EMNLP 2021. [pdf][code]

• ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning
  Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal.
  Proceedings of EMNLP 2021. [pdf (v2)][website]

• Integrating Visuospatial, Linguistic, and Commonsense Structure into Story Visualization
  Adyasha Maharana, Mohit Bansal.
  Proceedings of EMNLP 2021. [pdf][code]

• Inducing Transformer’s Compositional Generalization Ability via Auxiliary Sequence Prediction Tasks
  Yichen Jiang, Mohit Bansal.
  Proceedings of EMNLP 2021. [pdf][code]

• Continual Few-Shot Learning for Text Classification
  Ramakanth Pasunuru, Veselin Stoyanov, Mohit Bansal.
  Proceedings of EMNLP 2021. [pdf][code]

• FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging
  Han Guo, Nazneen Fatema Rajani, Peter Hase, Mohit Bansal, Caiming Xiong.
  Proceedings of EMNLP 2021. [pdf][code]

• NDH-Full: Learning and Evaluating Navigational Agents on Full-Length Dialogue
  Hyounghun Kim, Jialu Li, Mohit Bansal.
  Proceedings of EMNLP 2021. [pdf][code]

• Learning and Analyzing Generation Order for Undirected Sequence Models
  Yichen Jiang, Mohit Bansal.
  Findings of EMNLP 2021. [pdf][code]

• Improving and Simplifying Pattern Exploiting Training
  Derek Tam*, Rakesh R Menon*, Mohit Bansal, Shashank Srivastava and Colin Raffel.
  Proceedings of EMNLP 2021 (short). [pdf][code]

• iFacetSum: Coreference-based Interactive Faceted Summarization for Multi-Document Exploration
  Eran Hirsch, Alon Eirew, Ori Shapira, Avi Caciularu, Arie Cattan, Ori Ernst, Ramakanth Pasunuru, Hadar Ronen, Mohit Bansal, Ido Dagan.
  Proceedings of EMNLP 2021 (demo). [pdf][code+demo]

• Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline
  Ori Ernst, Ori Shapira, Ramakanth Pasunuru, Michael Lepioshkin, Jacob Goldberger, Mohit Bansal, Ido Dagan.
  Proceedings of CoNLL 2021 (colocated with EMNLP 2021). [pdf]
  (CoNLL Best Paper Runner-Up)

• To what extent do human explanations of model behavior align with actual model behavior?
  Grusha Prasad, Yixin Nie, Mohit Bansal, Robin Jia, Douwe Kiela, Adina Williams.
  Proceedings of BlackboxNLP Workshop, EMNLP 2021. [pdf][bib][code]

• An Overview of Uncertainty Calibration for Text Classification and the Role of Distillation
  Han Guo, Ramakanth Pasunuru, Mohit Bansal.
  Proceedings of RepL4NLP Workshop, ACL 2021. [pdf]

• Unifying Vision-and-Language Tasks via Text Generation
  Jaemin Cho, Jie Lei, Hao Tan, Mohit Bansal.
  Proceedings of ICML 2021. [pdf][code]

• EmailSum: Abstractive Email Thread Summarization
  Shiyue Zhang, Asli Celikyilmaz, Jianfeng Gao, Mohit Bansal.
  Proceedings of ACL 2021. [pdf][code]

• Continuous Language Generative Flow
  Zineng Tang, Shiyue Zhang, Hyounghun Kim, Mohit Bansal.
  Proceedings of ACL 2021. [pdf][code]

• mTVR: Multilingual Moment Retrieval in Videos
  Jie Lei, Tamara Berg, Mohit Bansal.
  Proceedings of ACL 2021 (short papers). [pdf][data/code]

• I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling
  Yixin Nie, Mary Williamson, Mohit Bansal, Douwe Kiela, Jason Weston.
  Proceedings of ACL 2021. [pdf][code]

• InfoSurgeon: Cross-Media Fine-grained Information Consistency Checking for Fake News Detection
  Yi Fung, Christopher Thomas, Revanth Gangi Reddy, Sandeep Polisetty, Heng Ji, Shih-Fu Chang, Kathleen McKeown, Mohit Bansal, Avi Sil.
  Proceedings of ACL 2021. [pdf][code]

• Analysis of Tree-Structured Architectures for Code Generation
  Samip Dahal, Adyasha Maharana, Mohit Bansal.
  Findings of ACL 2021 (short papers). [pdf]

• ChrEnTranslate: Cherokee-English Machine Translation Demo with Quality Estimation and Corrective Feedback
  Shiyue Zhang, Benjamin Frey and Mohit Bansal.
  Proceedings of ACL 2021 (demo papers). [pdf][demo][code]

• Disentangling Online Chats with DAG-structured LSTMs
  Duccio Pappadopulo*, Lisa Bauer*, Marco Farina, Ozan İrsoy, Mohit Bansal.
  Proceedings of *SEM 2021. [pdf]

• multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning
  Swarnadeep Saha, Prateek Yadav and Mohit Bansal.
  Proceedings of NAACL 2021. [pdf][code]

• Improving Generation and Evaluation of Visual Stories via Semantic Consistency
  Adyasha Maharana, Darryl Hannan and Mohit Bansal.
  Proceedings of NAACL 2021. [pdf][code]

• DeCEMBERT: Learning from Noisy Instructional Videos via Dense Captions and Entropy Minimization
  Zineng Tang*, Jie Lei* and Mohit Bansal.
  Proceedings of NAACL 2021. [pdf][code]

• Improving Cross-Modal Alignment in Vision Language Navigation via Syntactic Information
  Jialu Li, Hao Tan and Mohit Bansal.
  Proceedings of NAACL 2021 (short papers). [pdf][code]

• Dynabench: Rethinking Benchmarking in NLP
  Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts and Adina Williams.
  Proceedings of NAACL 2021. [pdf][website]

• Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization
  Yichen Jiang, Asli Celikyilmaz, Paul Smolensky, Paul Soulos, Sudha Rao, Hamid Palangi, Roland Fernandez, Caitlin Smith, Mohit Bansal, and Jianfeng Gao.
  Proceedings of NAACL 2021. [pdf][code]

• Efficiently Summarizing Text and Graph Encodings of Multi-Document Clusters
  Ramakanth Pasunuru, Mengwen Liu, Mohit Bansal, Sujith Ravi and Markus Dreyer.
  Proceedings of NAACL 2021. [pdf][code]

• Extending Multi-Document Summarization Evaluation to the Interactive Setting
  Ori Shapira, Ramakanth Pasunuru, Hadar Ronen, Mohit Bansal, Yael Amsterdamer and Ido Dagan.
  Proceedings of NAACL 2021. [pdf][bib][code]

• Robustness Gym: Unifying the NLP Evaluation Landscape
  Karan Goel, Nazneen Fatema Rajani, Jesse Vig, Zachary Taschdjian, Mohit Bansal and Christopher Ré.
  Proceedings of NAACL 2021 (demo papers). [pdf][bib][website]

• ERNIE-NLI: Analyzing the Impact of Domain-Specific External Knowledge on Enhanced Representations for NLI
  Lisa Bauer, Lingjia Deng, Mohit Bansal.
  Proceedings of DeeLIO Workshop, NAACL 2021. [pdf]

• GENE: Global Event Network Embedding
  Qi Zeng, Manling Li, Tuan Lai, Heng Ji, Mohit Bansal, Hanghang Tong.
  Proceedings of TextGraphs Workshop, NAACL 2021. [pdf]

• The Effect of Pretraining on Extractive Summarization for Scientific Documents
  Yash Gupta, Pawan Sasanka, Shikha Bordia, Arjun Manoharan, Deepak Mittal, Ramakanth Pasunuru, Manish Shrivastava, Maneesh Singh, Mohit Bansal, Preethi Jyothi.
  Proceedings of Scholarly Document Processing Workshop, NAACL 2021. [pdf]

• Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling (oral)
  Jie Lei*, Linjie Li*, Luowei Zhou, Zhe Gan, Tamara L. Berg, Mohit Bansal, Jingjing Liu.
  Proceedings of CVPR 2021. [pdf][bib][code]
  (CVPR Best Student Paper Honorable Mention)

• Identify, Align, and Integrate: Matching Knowledge Graphs to Commonsense Reasoning Tasks
  Lisa Bauer and Mohit Bansal.
  Proceedings of EACL 2021. [pdf][code]

• Hidden Biases in Unreliable News Detection Datasets
  Xiang Zhou, Heba Elfardy, Christos Christodoulopoulos, Thomas Butler and Mohit Bansal.
  Proceedings of EACL 2021. [pdf][code]
  (EACL Best Long Paper Honorable Mention)

• FixMyPose: Pose Correctional Captioning and Retrieval
  Hyounghun Kim*, Abhaysinh Zala*, Graham Burri, and Mohit Bansal.
  Proceedings of AAAI 2021. [pdf][code]

• Data Augmentation for Abstractive Query-Focused Multi-Document Summarization
  Ramakanth Pasunuru, Asli Celikyilmaz, Michel Galley, Chenyan Xiong, Yizhe Zhang, Mohit Bansal, and Jianfeng Gao.
  Proceedings of AAAI 2021. [pdf][code]

• Dual Reinforcement-Based Specification Generation for Image De-Rendering (oral)
  Ramakanth Pasunuru, David Rosenberg, Gideon Mann, and Mohit Bansal.
  Proceedings of Scientific Document Understanding Workshop, AAAI 2021. [pdf]

  2020

• ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
  Shiyue Zhang, Benjamin Frey, and Mohit Bansal.
  Proceedings of EMNLP 2020. [pdf][bib][data/code]

• Vokenization: Improving Language Understanding via Contextualized, Visually-Grounded Supervision
  Hao Tan and Mohit Bansal.
  Proceedings of EMNLP 2020. [pdf][bib][data/code][MIT Tech Review]

• What Can We Learn from Collective Human Opinions on Natural Language Inference Data?
  Yixin Nie, Xiang Zhou, and Mohit Bansal.
  Proceedings of EMNLP 2020. [pdf][bib][data/code]

• What Is More Likely To Happen Next? Video-and-Language Future Event Prediction
  Jie Lei, Licheng Yu, Tamara Berg, and Mohit Bansal.
  Proceedings of EMNLP 2020. [pdf][bib][data/code]

• ConjNLI: Natural Language Inference Over Conjunctive Sentences
  Swarnadeep Saha, Yixin Nie, and Mohit Bansal.
  Proceedings of EMNLP 2020. [pdf][bib][data/code]

• PRover: Proof Generation for Interpretable Reasoning over Rules
  Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava and Mohit Bansal.
  Proceedings of EMNLP 2020. [pdf][bib][code]

• DORB: Dynamically Optimizing Multiple Rewards with Bandits
  Ramakanth Pasunuru, Han Guo, and Mohit Bansal.
  Proceedings of EMNLP 2020. [pdf]

• The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions
  Xiang Zhou, Yixin Nie, Hao Tan, and Mohit Bansal.
  Proceedings of EMNLP 2020. [pdf][bib][code]

• Leakage-Adjusted Simulatability: Can Models Generate Non-Trivial Explanations of Their Behavior in Natural Language?
  Peter Hase, Shiyue Zhang, Harry Xie, and Mohit Bansal.
  Findings of EMNLP 2020. [pdf][bib][data/code]

• ArraMon: A Joint Navigation-Assembly Instruction Interpretation Task in Dynamic Environments
  Hyounghun Kim, Abhaysinh Zala, Graham Burri, Hao Tan, and Mohit Bansal.
  Findings of EMNLP 2020. [pdf][website]

• HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification
  Yichen Jiang*, Shikha Bordia*, Zheng Zhong, Charles Dognin, Maneesh Singh, and Mohit Bansal.
  Findings of EMNLP 2020. [pdf] [website]

• Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension
  Adyasha Maharana and Mohit Bansal.
  Findings of EMNLP 2020. [pdf]

• FENAS: Flexible and Expressive Neural Architecture Search
  Ramakanth Pasunuru and Mohit Bansal.
  Findings of EMNLP 2020 (short papers). [pdf]

• TVR: A Large-Scale Dataset for Video-Subtitle Moment Retrieval
  Jie Lei, Licheng Yu, Tamara L. Berg, and Mohit Bansal.
  Proceedings of ECCV 2020, Glasgow, UK. [pdf][bib][website]

• Diagnosing the Environment Bias in Vision-and-Language Navigation
  Yubo Zhang*, Hao Tan*, and Mohit Bansal.
  Proceedings of IJCAI 2020, Yokohama, Japan. [pdf][bib][code/data]

• Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?
  Peter Hase and Mohit Bansal.
  Proceedings of ACL 2020, Seattle, WA. [pdf][bib][code/data]

• Towards Robustifying NLI Models Against Lexical Dataset Biases
  Xiang Zhou and Mohit Bansal.
  Proceedings of ACL 2020, Seattle, WA. [pdf][bib][code/data]

• Adversarial NLI: A New Benchmark for Natural Language Understanding
  Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, and Douwe Kiela.
  Proceedings of ACL 2020, Seattle, WA. [pdf][bib][data][demo]

• Dense-Caption Matching and Frame-Selection Gating for Temporal Localization in VideoQA
  Hyounghun Kim, Zineng Tang, and Mohit Bansal.
  Proceedings of ACL 2020, Seattle, WA. [pdf][bib][code]

• MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
  Jie Lei, Liwei Wang, Yelong Shen, Dong Yu, Tamara Berg, and Mohit Bansal.
  Proceedings of ACL 2020, Seattle, WA. [pdf][bib][code/data]

• TVQA+: Spatio-Temporal Grounding for Video Question Answering
  Jie Lei, Licheng Yu, Tamara L. Berg, and Mohit Bansal.
  Proceedings of ACL 2020, Seattle, WA. [pdf v2][bib][data]

• Simple Compounded-Label Training for Fact Extraction and Verification
  Yixin Nie*, Lisa Bauer*, Mohit Bansal.
  Proceedings of Fact Extraction and VERification (FEVER) workshop, ACL 2020, Seattle, WA. [pdf][bib]

• Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits
  Han Guo, Ramakanth Pasunuru, and Mohit Bansal.
  Proceedings of AAAI 2020, New York, NY. [pdf][bib]
  

• ManyModalQA: Modality Disambiguation and QA over Diverse Inputs
  Darryl Hannan, Akshay Jain, and Mohit Bansal.
  Proceedings of AAAI 2020, New York, NY. [pdf][bib]
  

• AvgOut: A Simple Output-Probability Measure to Eliminate Dull Responses
  Tong Niu and Mohit Bansal.
  Proceedings of AAAI 2020, New York, NY. [pdf][bib]
  

• Modality-Balanced Models for Visual Dialogue
  Hyounghun Kim, Hao Tan, and Mohit Bansal.
  Proceedings of AAAI 2020, New York, NY. [pdf][bib]
  

• Enabling Robots to Understand Incomplete Natural Language Instructions Using Commonsense Reasoning
  Haonan Chen, Hao Tan, Alan Kuntz, Mohit Bansal, Ron Alterovitz.
  Proceedings of ICRA 2020, Paris, France. [pdf][bib][demo video]

  2019

• LXMERT: Learning Cross-Modality Encoder Representations from Transformers
  Hao Tan and Mohit Bansal.
  Proceedings of EMNLP 2019, Hong Kong. [pdf][bib][code]
  

• Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning
  Yichen Jiang and Mohit Bansal.
  Proceedings of EMNLP 2019, Hong Kong. [pdf][bib][code]
  

• Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering
  Shiyue Zhang and Mohit Bansal.
  Proceedings of EMNLP 2019, Hong Kong. [pdf][bib][code]
  

• Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
  Yixin Nie, Songhe Wang, and Mohit Bansal.
  Proceedings of EMNLP 2019, Hong Kong. [pdf][bib][code]
  

• Automatically Learning Data Augmentation Policies for Dialogue Tasks
  Tong Niu and Mohit Bansal.
  Proceedings of EMNLP 2019, Hong Kong (short papers). [pdf][bib]
  

• Continual and Multi-Task Architecture Search
  Ramakanth Pasunuru and Mohit Bansal.
  Proceedings of ACL 2019, Florence, Italy. [pdf][bib][code]
  

• Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA
  Yichen Jiang and Mohit Bansal.
  Proceedings of ACL 2019, Florence, Italy. [pdf][bib][data/code]

• Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension
  Yichen Jiang*, Nitish Joshi*, Yen-Chun Chen, and Mohit Bansal.
  Proceedings of ACL 2019, Florence, Italy. [pdf][bib][code]

• Expressing Visual Relationships via Language
  Hao Tan, Franck Dernoncourt, Zhe Lin, Trung Bui, and Mohit Bansal.
  Proceedings of ACL 2019, Florence, Italy. [pdf][bib][data/code]

• Improving Visual Question Answering by Referring to Generated Paragraph Captions
  Hyounghun Kim and Mohit Bansal.
  Proceedings of ACL 2019, Florence, Italy (short papers). [pdf][bib]
  (ACL Best Short Paper Nominee)

• PaperRobot: Incremental Draft Generation of Scientific Ideas
  Qingyun Wang, Lifu Huang, Zhiying Jiang, Kevin Knight, Heng Ji, Mohit Bansal, and Yi Luan.
  Proceedings of ACL 2019, Florence, Italy. [pdf][bib][code]

• Learning to Navigate Unseen Environments: Back Translation with Environmental Dropout
  Hao Tan, Licheng Yu, and Mohit Bansal.
  Proceedings of NAACL 2019, Minneapolis, MN. [pdf][bib][code]
  (1st Rank Model in Room-to-Room Vision-Language-Navigation Challenge)

• AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning
  Han Guo, Ramakanth Pasunuru, and Mohit Bansal.
  Proceedings of NAACL 2019, Minneapolis, MN. [pdf][bib][code]
  

• Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation
  Ori Shapira, David Gabay, Yang Gao, Hadar Ronen, Ramakanth Pasunuru, Mohit Bansal, Yael Amsterdamer, and Ido Dagan.
  Proceedings of NAACL 2019, Minneapolis, MN (short papers). [pdf][bib][code]
  

• Multi-Target Embodied Question Answering
  Licheng Yu, Xinlei Chen, Georgia Gkioxari, Mohit Bansal, Tamara L. Berg, and Dhruv Batra.
  Proceedings of CVPR 2019, Long Beach, CA. [pdf][bib][video]
  

• Efficient Generation of Motion Plans from Attribute-Based Natural Language Instructions Using Dynamic Constraint Mapping
  Jae Sung Park, Biao Jia, Mohit Bansal, and Dinesh Manocha
  Proceedings of ICRA 2019, Montreal, Canada. [pdf][bib][demo]

• Combining Fact Extraction and Verification with Neural Semantic Matching Networks
  Yixin Nie, Haonan Chen, and Mohit Bansal.
  Proceedings of AAAI 2019, Honolulu, HI. [pdf][bib][code]

• Analyzing Compositionality-Sensitivity of NLI Models
  Yixin Nie*, Yicheng Wang*, and Mohit Bansal.
  Proceedings of AAAI 2019, Honolulu, HI. [pdf][bib][data/code]

• DSTC7-AVSD: Scene-Aware Video-Dialogue Systems with Dual Attention
  Ramakanth Pasunuru and Mohit Bansal
  Proceedings of Dialog System Technology Challenges Workshop, AAAI 2019, Honolulu, Hawaii. [pdf][bib]
  (Selected Oral)

  2018

• Closed-Book Training to Improve Summarization Encoder Memory
  Yichen Jiang and Mohit Bansal.
  Proceedings of EMNLP 2018, Brussels, Belgium. [pdf][bib]

• SafeCity: Understanding Diverse Forms of Sexual Harassment Personal Stories
  Sweta Karlekar and Mohit Bansal.
  Proceedings of EMNLP 2018, Brussels, Belgium (short papers). [pdf][bib][data]

• Commonsense for Generative Multi-Hop Question Answering Tasks
  Lisa Bauer*, Yicheng Wang*, and Mohit Bansal.
  Proceedings of EMNLP 2018, Brussels, Belgium. [pdf][bib]

• Game-Based Video-Context Dialogue
  Ramakanth Pasunuru and Mohit Bansal.
  Proceedings of EMNLP 2018, Brussels, Belgium. [pdf (v2)][bib][data/code]

• TVQA: Localized, Compositional Video Question Answering
  Jie Lei, Licheng Yu, Mohit Bansal, and Tamara Berg.
  Proceedings of EMNLP 2018, Brussels, Belgium. [pdf][bib][website]

• Incorporating Background Knowledge into Video Description Generation
  Spencer Whitehead, Heng Ji, Mohit Bansal, Shih-Fu Chang, and Clare Voss.
  Proceedings of EMNLP 2018, Brussels, Belgium. [pdf][bib]

• Adversarial Over-Sensitivity and Over-Stability Strategies for Dialogue Models
  Tong Niu and Mohit Bansal.
  Proceedings of CoNLL 2018, Brussels, Belgium. [pdf][bib][code]

• Combining Fact Extraction and Claim Verification in an NLI Model
  Yixin Nie, Haonan Chen, and Mohit Bansal.
  In Fact Extraction and Verification (FEVER) Workshop (non-archival), EMNLP 2018, Brussels, Belgium.
  (extended AAAI version: [pdf])
  (1st Rank Model in Shared Task) [Press Article]

• Dynamic Multi-Level Multi-Task Learning for Sentence Simplification
  Han Guo, Ramakanth Pasunuru, and Mohit Bansal.
  Proceedings of COLING 2018, Santa Fe, New Mexico. [pdf][bib][code]
  (Area Chair Favorites)

• Polite Dialogue Generation Without Parallel Data
  Tong Niu and Mohit Bansal.
  Proceedings of TACL 2018. Presented at EMNLP 2018, Brussels, Belgium. [pdf][bib][code]

• Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting
  Yen-Chun Chen and Mohit Bansal.
  Proceedings of ACL 2018, Melbourne, Australia. [pdf][bib][code]

• Soft, Layer-Specific Multi-Task Summarization with Entailment and Question Generation
  Han Guo*, Ramakanth Pasunuru*, and Mohit Bansal.
  Proceedings of ACL 2018, Melbourne, Australia. [pdf][bib]

• #MeToo: Neural Detection and Explanation of Language in Personal Abuse Stories
  Sweta Karlekar and Mohit Bansal.
  Proceedings of WiNLP 2018 (Widening NLP Workshop), NAACL 2018, New Orleans, LA. [pdf][bib]

• Object Ordering with Bidirectional Matchings for Visual Reasoning
  Hao Tan and Mohit Bansal.
  Proceedings of NAACL 2018, New Orleans, LA (short papers). [pdf][bib]
  (Top Model in Image Challenge)
  

• Multi-Reward Reinforced Summarization with Saliency and Entailment
  Ramakanth Pasunuru and Mohit Bansal.
  Proceedings of NAACL 2018, New Orleans, LA (short papers). [pdf][bib]

• Detecting Linguistic Characteristics of Alzheimer's Dementia by Interpreting Neural Models
  Sweta Karlekar, Tong Niu, and Mohit Bansal.
  Proceedings of NAACL 2018, New Orleans, LA (short papers). [pdf][bib]

• Robust Machine Comprehension Models via Adversarial Training
  Yicheng Wang and Mohit Bansal.
  Proceedings of NAACL 2018, New Orleans, LA (short papers). [pdf][bib]

• Punny Captions: Witty Wordplay in Image Descriptions
  Arjun Chandrasekaran, Devi Parikh, and Mohit Bansal.
  Proceedings of NAACL 2018, New Orleans, LA (short papers). [pdf][bib]

• Joint Modeling of Text and Acoustic-Prosodic Cues for Neural Parsing
  Trang Tran*, Shubham Toshniwal*, Mohit Bansal, Kevin Gimpel, Karen Livescu, and Mari Ostendorf.
  Proceedings of NAACL 2018, New Orleans, LA. [pdf][bib]

• MAttNet: Modular Attention Network for Referring Expression Comprehension
  Licheng Yu, Zhe Lin, Xiaohui Shen, Jimei Yang, Xin Lu, Mohit Bansal, Tamara Berg.
  Proceedings of CVPR 2018, Salt Lake City, UT. [pdf][bib][DEMO]

• Source-Target Inference Models for Spatial Instruction Understanding
  Hao Tan and Mohit Bansal.
  Proceedings of AAAI 2018, New Orleans, LA. [pdf][bib]

• Retweet Wars: Tweet Popularity Prediction via Multimodal Regression
  Ke Wang, Mohit Bansal, and Jan-Michael Frahm.
  Proceedings of WACV 2018, Lake Tahoe, CA. [pdf][bib]

  2017

• Interactive-Length Multi-Task Video Captioning with Cooperative Feedback
  Han Guo, Ramakanth Pasunuru, and Mohit Bansal.
  Proceedings of NIPS 2017, Long Beach, CA (demo papers). [pdf][bib]

• Reinforced Video Captioning with Entailment Rewards
  Ramakanth Pasunuru and Mohit Bansal.
  Proceedings of EMNLP 2017, Copenhagen, Denmark (short papers). [pdf][bib][code]

• Hierarchically-Attentive RNN for Album Summarization and Storytelling
  Licheng Yu, Mohit Bansal, and Tamara Berg.
  Proceedings of EMNLP 2017, Copenhagen, Denmark (short papers). [pdf][bib]

• Video Highlight Prediction Using Audience Chat Reactions
  Cheng-Yang Fu, Joon Lee, Mohit Bansal, and Alexander Berg.
  Proceedings of EMNLP 2017, Copenhagen, Denmark (short papers). [pdf][bib][code/data]

• Shortcut-Stacked Sentence Encoders for Multi-Domain Inference
  Yixin Nie and Mohit Bansal.
  Proceedings of RepEval Workshop, EMNLP 2017, Copenhagen, Denmark. [pdf][bib][code]
  (Top Single Model in Shared Task)

• Towards Improving Abstractive Summarization via Entailment Generation
  Ramakanth Pasunuru, Han Guo, and Mohit Bansal.
  Proceedings of Workshop on Summarization Frontiers, EMNLP 2017, Copenhagen, Denmark. [pdf][bib]
  (Contributed Talk)

• Multi-Task Video Captioning with Video and Entailment Generation
  Ramakanth Pasunuru and Mohit Bansal.
  Proceedings of ACL 2017, Vancouver, Canada. [pdf][bib]
  (ACL Outstanding Paper Award)

• A Joint Speaker-Listener-Reinforcer Model for Referring Expressions
  Licheng Yu, Hao Tan, Mohit Bansal, and Tamara L. Berg.
  Proceedings of CVPR 2017, Honolulu, HI. [pdf][bib]
  (Spotlight; 8% acceptance rate)

• Navigational Instruction Generation as Inverse Reinforcement Learning with Neural Machine Translation
  Andrea F. Daniele, Mohit Bansal, and Matthew R. Walter.
  Proceedings of HRI 2017 (Human-Robot Interaction), Vienna, Austria. [pdf][bib]

• Contextual RNN-GANs for Abstract Reasoning Diagram Generation
  Arnab Ghosh, Viveka Kulharia, Amitabha Mukerjee, Vinay Namboodiri, and Mohit Bansal.
  Proceedings of AAAI 2017, San Francisco, CA. [pdf][bib]

• Coherent Dialogue with Attention-based Language Models
  Hongyuan Mei, Mohit Bansal, and Matthew Walter.
  Proceedings of AAAI 2017, San Francisco, CA. [pdf][bib]

  2016

• Interpreting Neural Networks to Improve Politeness Comprehension
  Malika Aubakirova and Mohit Bansal.
  Proceedings of EMNLP 2016, Austin, TX (short papers). [pdf][bib]

• Sort Story: Sorting Jumbled Images and Captions into Stories
  Harsh Agrawal, Arjun Chandrasekaran, Dhruv Batra, Devi Parikh, and Mohit Bansal.
  Proceedings of EMNLP 2016, Austin, TX (short papers). [pdf][bib]

• Question Relevance in VQA: Identifying Non-Visual And False-Premise Questions
  Arijit Ray, Gordon Christie, Mohit Bansal, Dhruv Batra, and Devi Parikh.
  Proceedings of EMNLP 2016, Austin, TX (short papers). [pdf][bib]

• Who did What: A Large-Scale Person-Centered Cloze Dataset
  Takeshi Onishi, Hai Wang, Mohit Bansal, Kevin Gimpel, and David McAllester.
  Proceedings of EMNLP 2016, Austin, TX (short papers). [pdf][bib]

• Charagram: Embedding Words and Sentences via Character n-grams
  John Wieting, Mohit Bansal, Kevin Gimpel, and Karen Livescu.
  Proceedings of EMNLP 2016, Austin, TX. [pdf][bib][code]

• End-to-end Relation Extraction using LSTMs on Sequences and Tree Structures
  Makoto Miwa and Mohit Bansal.
  Proceedings of ACL 2016, Berlin, Germany. [pdf][bib][code]

• Mapping Unseen Words to Task-Trained Embedding Spaces
  Pranava Swaroop Madhyastha, Mohit Bansal, Kevin Gimpel, and Karen Livescu.
  Proceedings of Workshop on Representation Learning for NLP, ACL 2016, Berlin, Germany [pdf][bib]
  (Best Paper Award)

• What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment
  Hongyuan Mei, Mohit Bansal, and Matthew R. Walter.
  Proceedings of NAACL 2016, San Diego, CA. [pdf][bib]

• The Role of Context Types and Dimensionality in Learning Word Embeddings
  Oren Melamud, David McClosky, Siddharth Patwardhan, and Mohit Bansal.
  Proceedings of NAACL 2016, San Diego, CA. [pdf][bib]

• We Are Humor Beings: Understanding and Predicting Visual Humor
  Arjun Chandrasekaran, Ashwin Kalyan, Stanislaw Antol, Mohit Bansal, Dhruv Batra, C. Lawrence Zitnick, and Devi Parikh.
  Proceedings of CVPR 2016, Las Vegas, Nevada. [pdf][bib][data]
  (Spotlight; 9.7% acceptance rate)

• Towards Universal Paraphrastic Sentence Embeddings
  John Wieting, Mohit Bansal, Kevin Gimpel, and Karen Livescu.
  Proceedings of ICLR 2016, San Juan, Puerto Rico. [pdf][bib][data/code]
  (Oral; 5.7% acceptance rate)

• Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences
  Hongyuan Mei, Mohit Bansal, and Matthew R. Walter.
  Proceedings of AAAI 2016, Phoenix, Arizona. [pdf][bib]
  (NVidia Paper Award in NIPS 2015 Multimodal Machine Learning workshop)

  2015

• Machine Comprehension with Syntax, Frames, and Semantics
  Hai Wang, Mohit Bansal, Kevin Gimpel, and David McAllester.
  Proceedings of ACL 2015, Beijing, China (short papers). [pdf][bib]

• From Paraphrase Database to Compositional Paraphrase Model and Back
  John Wieting, Mohit Bansal, Kevin Gimpel, Karen Livescu, and Dan Roth.
  Proceedings of TACL. To be presented at EMNLP 2015, Lisbon, Portugal.[pdf][bib][data/code]
  [pdf v2 (see Appendix A)][new 300-dim embeddings]

• Dependency Link Embeddings: Continuous Representations of Syntactic Substructures
  Mohit Bansal.
  Proceedings of Workshop on Vector Space Modeling for NLP (selected oral), NAACL 2015, Denver, Colorado.[pdf][slides][bib][data]
  

• Deep Multilingual Correlation for Improved Word Embeddings
  Ang Lu, Weiran Wang, Mohit Bansal, Kevin Gimpel, and Karen Livescu.
  Proceedings of NAACL 2015, Denver, Colorado (short papers).[pdf][bib][code]

• A Sense-Topic Model for Word Sense Induction with Unsupervised Data Enrichment
  Jing Wang, Mohit Bansal, Kevin Gimpel, Brian Ziebart, and Clement Yu.
  Proceedings of TACL. Presented at NAACL 2015, Denver, Colorado.[pdf][bib]

• Accurate Vision-based Vehicle Localization using Satellite Imagery
  Hang Chu, Hongyuan Mei, Mohit Bansal, and Matthew R. Walter.
  Proceedings of NIPS 2015 Workshop on Transfer and Multi-Task Learning, Montreal, Canada.[pdf][bib]

  2014

• Weakly-Supervised Learning with Cost-Augmented Contrastive Estimation
  Kevin Gimpel and Mohit Bansal.
  Proceedings of EMNLP 2014. Doha, Qatar.[pdf][supplementary][bib]

• Tailoring Continuous Word Representations for Dependency Parsing
  Mohit Bansal, Kevin Gimpel, and Karen Livescu.
  Proceedings of ACL 2014. Baltimore, MD, USA (short papers).[pdf][slides][bib][data]

• Structured Learning for Taxonomy Induction with Belief Propagation
  Mohit Bansal, David Burkett, Gerard de Melo, and Dan Klein.
  Proceedings of ACL 2014. Baltimore, MD, USA.[pdf, errata][slides][bib][data]
  (ACL Best Paper Award Honorable Mention)

• What are you talking about? Text-to-Image Coreference
  Chen Kong, Dahua Lin, Mohit Bansal, Raquel Urtasun, and Sanja Fidler.
  Proceedings of CVPR 2014. Columbus, OH, USA.[pdf][bib][data/code]

  2013 — 2009

• Good, Great, Excellent: Global Inference of Semantic Intensities
  Gerard de Melo and Mohit Bansal.
  Proceedings of TACL. Presented at ACL 2013. Sofia, Bulgaria.[pdf][slides][bib][data/code]

• Coreference Semantics from Web Features
  Mohit Bansal and Dan Klein.
  Proceedings of ACL 2012. Jeju, South Korea.[pdf][slides][bib][code]

• Unsupervised Translation Sense Clustering
  Mohit Bansal, John DeNero, and Dekang Lin.
  Proceedings of NAACL 2012. Montreal, Canada.[pdf][slides][bib]

• Web-Scale Features for Full-Scale Parsing
  Mohit Bansal and Dan Klein.
  Proceedings of ACL 2011. Portland, OR, USA.[pdf, errata][slides][bib]

• Gappy Phrasal Alignment By Agreement
  Mohit Bansal, Chris Quirk, and Robert Moore.
  Proceedings of ACL 2011. Portland, OR, USA.[pdf][slides][bib]

• The Surprising Variance in Shortest-Derivation Parsing
  Mohit Bansal and Dan Klein.
  Proceedings of ACL 2011. Portland, OR, USA (short papers).[pdf][bib]

• Mention Detection: Heuristics for the OntoNotes annotations
  Jonathan K. Kummerfeld, Mohit Bansal, David Burkett, and Dan Klein.
  Proceedings of CoNLL 2011 (shared task). Portland, OR, USA.[pdf][bib]

• Simple, Accurate Parsing with an All-Fragments Grammar
  Mohit Bansal and Dan Klein.
  Proceedings of ACL 2010. Uppsala, Sweden.[pdf][slides][bib]

• Efficient Parsing for Transducer Grammars
  John DeNero, Mohit Bansal, Adam Pauls, and Dan Klein.
  Proceedings of NAACL 2009. Boulder, CO, USA.[pdf][slides][bib]

  2008 — 2007

• The power of negative thinking: Exploiting label disagreement in the min-cut classification framework
  Mohit Bansal, Claire Cardie, and Lillian Lee.
  Proceedings of COLING 2008. Manchester, UK (short papers).[pdf][slides][bib]

• Estimating Hybrid Frequency Moments of Data Streams
  Sumit Ganguly, Mohit Bansal, and Shruti Dube.
  Proceedings of FAW 2008. Changsha, China.
  Also accepted in the Journal of Combinatorial Optimization (JOCO).[pdf][bib]

• Text Processing for Text-to-Speech Systems in Indian Languages
  Anand A Raj, Tanuja Sarkar, Satish C Pammi, Santhosh Yuvaraj, Mohit Bansal, Kishore Prahallad, and Alan W Black.
  Proceedings of ISCA SSW6 2007. Bonn, Germany.[pdf][bib]

• OTHERS:
  
  
• Learning Articulated Motion Models from Visual and Lingual Signals
  Zhengyang Wu, Mohit Bansal, and Matthew R. Walter.
  Preprint arXiv:1511.05526, 2016. [pdf][bib]
• Web-scale Surface and Syntactic n-gram Features for Dependency Parsing
  Dominick Ng, Mohit Bansal, and James R. Curran.
  Preprint arXiv:1502.07038, 2015. [pdf][bib][code]

• THESES:
  
  Surface Web Semantics for Structured Natural Language Processing
  Mohit Bansal, Ph.D. Thesis. EECS, UC Berkeley.
  Committee: Dan Klein (chair), Marti Hearst, Line Mikkelsen, Nelson Morgan.[pdf]

• An All-Fragments Grammar for Simple and Accurate Parsing
  Mohit Bansal, M.S. Thesis. EECS, UC Berkeley.
  Advisor: Dan Klein.[pdf]

• Patents:
  
  Techniques for generating translation clusters
  John DeNero and Mohit Bansal.
  Publication number: US20130275118 A1 (Oct 17, 2013)

Teaching

Instructor, COMP590/790: Connecting Language to Vision and Robotics, UNC Chapel Hill, Spring 2023.

Instructor, COMP590/790: Connecting Language to Vision and Robotics, UNC Chapel Hill, Fall 2021.

Instructor, COMP786: Natural Language Processing, UNC Chapel Hill, Fall 2020.

Instructor, First-Year Undergraduate Honors Seminar: Special Topics: Human and Artificial Intelligence Through the Prism of Language, Fall 2019.

Instructor, Advanced Topics in NLP: Recent Progress in Different Learning Paradigms, UNC Chapel Hill, Spring 2019.

Instructor, Advanced Topics in NLP: Conversational Models, UNC Chapel Hill, Spring 2018.

Instructor, Graduate Natural Language Processing, UNC Chapel Hill, Fall 2017.

Instructor, Advanced Topics in NLP: Language Grounding for Robotics, UNC Chapel Hill, Spring 2017.

Instructor, Seminar on Natural Language Processing, UNC Chapel Hill, Fall 2016.

Guest Lecturer, Computational Linguistics (Instructor: John Goldsmith), University of Chicago, Spring 2015.

Guest Lecturer, Robotics and Artificial Intelligence (Instructor: Matthew Walter), TTI-Chicago, University of Chicago, Spring 2015.

Guest Lecturer, Visual Recognition with Text (Instructor: Sanja Fidler), University of Toronto, Winter 2015 — short course on 'Topics, Trends, and Resources in NLP' [slides].

Grad Student Instructor, Introduction to Artificial Intelligence (Instructor: Dan Klein), UC Berkeley, Fall 2011. Received an Outstanding Graduate Student Instructor Award by UC Berkeley for excellence in teaching.

Grad Student Instructor, Advanced Topics in Artificial Intelligence (Instructors: Pieter Abbeel, Dan Klein, Jitendra Malik), UC Berkeley, Spring 2009. Sole TA for new course with 30 advanced students.

Recent Invited Talks/Keynotes:

Distinguished Lecture Series, StonyBrook [New: 'Planning Agents for Collaborative Reasoning and Multimodal Generation']

Distinguished Speaker Series, USF

Keynote, Amazon Research Days

Keynote, TTIC Multimodal AI Workshop

Keynote, Lisbon Machine Learning Summer School (LxMLS) 2024

Keynote, 12th International Advanced Summer School on NLP (IASNLP-2024)

Invited Speaker, 1st Korea NLP/LM Workshop

Keynote, Pinterest Labs ML Symposium 2024

Keynote, Lisbon Machine Learning Summer School (LxMLS) 2024

Distinguished Lecture Series, USC ['Multimodal Generative Models: Unification, Planning Agents, Evaluation']

Keynote, SouthNLP Symposium 2024

Invited Speaker, IndoML 2023

IISc Bangalore (Kotak AI-ML Centre)

Keynote, 27th Conference on Computational Natural Language Learning (CoNLL 2023) ['Multimodal Generative LLMs: Unification, Interpretability, Evaluation': video]

Invited Speaker, TTIC 20th Anniversary Celebration

Keynote, AACL-IJCNLP 2023

Penn State NLP Colloquium Series

Auburn AI Distinguished Speaker Series, 2023

TWIML AI Podcast: 'Unifying Vision and Language Models'

ACL 2023 Narrative Understanding Workshop

CVPR 2023 Explainable AI for Computer Vision (XAI4CV) Workshop

IBM Neuro-Symbolic AI Workshop 2023 ['Modeling and Evaluating Faithful Generation in Language (and Vision)']

MBZUAI AI Quorum's Inaugural NLP Symposium ['Unified and Efficient Vision-and-Language Modeling': video]

UT Austin Forum for Artificial Intelligence

Stanford NLP Seminar

Open Data Science Conference

ICML 2022 Pre-training Workshop ['Unified and Efficient Multimodal Pretraining Across Vision and Language': video]

Keynote, 15th International Conference on Natural Language Generation (INLG 2022) ['Modeling and Evaluating Faithful Generation in Language (and Vision)': video]

Robustness in Sequential Data (ROSE) Workshop, CVPR 2022

Summarization of Creative Text Workshop, COLING 2022

Indian Symposium on Machine Learning (IndoML), 2021 ['Knowledgeable and Spatio-Temporal Vision+Language': video]

Fact Extraction and VERification (FEVER) Workshop, EMNLP 2021

Closing the Loop Between Vision and Language (CLVL) Workshop, ICCV 2021 ['Knowledgeable and Spatio-Temporal Vision+Language': video]

Human Interaction for Robotic Navigation Workshop, ICCV 2021 ['Video and Embodied Grounding for Language': video]

CVIT Summer School on Artificial Intelligence, 2021

Advances in Language and Vision Research (ALVR) Workshop, NAACL 2021

Person in Context Workshop, CVPR 2021

VQA Workshop, CVPR 2021 ['Knowledgeable and Spatio-Temporal Vision+Language': video, slides]

IJCAI 2020 Early Career Spotlight Talk

Singapore Symposium on Natural Language Processing (SSNLP 2020) ['Towards Knowledge-Robust and Multimodally-Grounded NLP': video]

3rd Workshop on Neural Generation and Translation (WNGT @ EMNLP 2019) ['Knowledgeable and Multimodal Language Generation': slides]

1st Workshop on Beyond Vision and Language: Integrating Knowledge from Real-World (LANTERN @ EMNLP 2019) ['Knowledgeable and Dynamic Spatio-Temporal Language+Vision+Robotics': slides]

Workshop on Machine Reading for Question Answering (MRQA @ EMNLP 2019) ['Interpretability and Robustness for Multi-Hop QA': slides]

4th Workshop on Representation Learning for NLP (RepL4NLP @ ACL 2019) ['Knowledgeable and Adversarially-Robust Representation Learning': slides]

RSS-2018 Natural Human-Robot Communication Workshop ['Spatially-Grounded, Personable, and Sensible Human-Robot Communication']

Triangle ML Day

Google Assistant Dialog Workshop

Machine Learning Summer School

SAS-Nvidia Deep Learning Symposium

ML@GeorgiaTech Seminar

Kenan-InfiaML-Rethinc Machine Learning Symposium

UNC Alumni AI Panel

Students/Interns

Student openings: I am looking for highly motivated PhD students. If you are interested in the broad areas of multimodal NLP (with vision and speech, for robotics), language generation and dialogue/Q&A, and structured+interpretable deep learning, please see my prospective student page and contact me at mbansal-AT-cs-DOT-unc-DOT-edu for further details.

More student info at: MURGe-Lab

UNC Advisees:
Shiyue Zhang (UNC, PhD) (Bloomberg Data Science PhD Fellow)
Xiang Zhou (UNC, PhD)
Peter Hase (UNC, PhD) (Google PhD Fellow)
Yichen Jiang (UNC, PhD) (Apple AI/ML PhD Fellow)
Adyasha Maharana (UNC, PhD)
Swarnadeep Saha (UNC, PhD) (Google PhD Fellow)
Jaemin Cho (UNC, PhD)
Jialu Li (UNC, PhD)
Prateek Yadav (UNC, PhD)
Archiki Prasad (UNC, PhD)
Yi-Lin Sung (UNC, PhD)
David Wan (UNC, PhD)
Vaidehi Patil (UNC, PhD)
Ziyang Wang (UNC, PhD)
Shoubin Yu (UNC, PhD)

Abhay Zala (UNC, MS)
Zhuofan Ying (UNC, BS)
Zineng Tang (UNC, BS) (CRA Outstanding Undergraduate Researcher Award 2023)
Hanna Tischer (UNC, BS)

Past Advisees:
Lisa Bauer (UNC, PhD) (NSF Graduate Research Fellow) --> Research Scientist, Amazon AI
Hyounghun Kim (UNC, PhD) --> Assistant Professor, UNIST
Jie Lei (UNC, PhD; co-advisor: Tamara Berg) (Adobe Research Fellow) --> Research Scientist, Facebook AI
Yixin Nie (UNC, PhD) --> Research Scientist, Facebook AI
Darryl Hannan (UNC, MS) --> AI Engineer, Drexel
Ramakanth Pasunuru (UNC, PhD) (Microsoft Research PhD Fellow; Facebook PhD Fellowship Finalist) --> Research Scientist, FAIR Lab, Meta
Hao Tan (UNC, PhD) (Bloomberg Data Science PhD Fellow) --> Research Scientist, Adobe Research
Yen-Chun Chen (UNC, MS) --> Researcher, Microsoft Research
Tong Niu (Visiting student; Duke, MS) --> Research Scientist, Salesforce Research
Licheng Yu (UNC, PhD; advisor = Tamara Berg) --> Research Scientist, Facebook AI

Han Guo (UNC, BS) (CRA Outstanding Undergraduate Researcher Award Finalist, 2020) --> PhD Student, CMU
Sweta Karlekar (UNC, BS) (CRA Outstanding Undergraduate Researcher Award Runner-Up, 2020) --> ML Engineer, Facebook
Yinuo (Eva) Hu (UNC, BS) (Highest Honors) --> MS, UC Berkeley
Samip Dahal (UNC, BS) --> Replit
Antonio Mendoza (UNC, BS) --> Verisk Analytics
Tsion Coulter (UNC, BS) --> Deloitte
Songhe Wang (UNC, BS) --> PhD Student, Penn State
Yicheng Wang (UNC, BS) --> Software Engineer, JaneStreet
Nitish Joshi (Visiting student; IIT Bombay, BS) --> PhD Student, NYU

Malika Aubakirova (UChicago, BS)
Arjun Chandrasekaran (Visiting Student; Georgia Tech, PhD; advisor = Devi Parikh)
Dhivya Eswaran (IIT-Madras, BTech --> CMU, PhD)
Rasool Fakoor (UT-Arlington, PhD --> MSR)
Arnab Ghosh (IIT Kanpur, BTech --> Oxford, PhD)
Yuchen He (UIUC, PhD)
Myungin Kim (UChicago, MS)
Zuyao Li (USC, MS --> Google/Nest)
Ang Lu (Tsinghua, BS --> CMU, MS)
Pranava S. Madhyastha (UPC Barcelona, PhD)
Hongyuan Mei (UChicago/TTIC, MS --> JHU, PhD) (MS Thesis Co-Advisor)
Aravind L Srinivas (IIT Madras, BTech --> UC Berkeley, PhD)
Ryan Stout (UIUC, MS)
Trang Tran (UWash, PhD)
Jing Wang (UIC, PhD --> Conversant)
John Wieting (UIUC/TTIC MS --> CMU, PhD)
Zhengyang Wu (GeorgiaTech, BS --> MagicLeap)

Professional Service

Program Chair, EMNLP 2024

Member, ACL Executive Committee (2022-2024)

Member, ACM Doctoral Dissertation Award Committee (2021-2024)

Action Editor, TACL Journal

Action Editor, Computational Linguistics (CL) Journal

Associate Editor, IEEE/ACM Transactions on Audio Speech and Language Processing (TASLP)

Editorial Board, Computer Speech and Language Journal

Americas Sponsorship Co-Chair for the ACL (2020-2022)

Senior Area Chair: EACL 2024

Senior Area Chair: EMNLP 2023

Senior Area Chair: ACL Rolling Review (ARR)

Senior Area Chair: IJCAI 2023

Senior Area Chair: AAAI 2023

Area Chair: NeurIPS 2022

Senior Area Chair: ACL 2022

Area Chair: ICLR 2022

Senior Area Chair (Vision, Robotics, Grounding): ACL 2021

Senior Area Chair (Vision, Robotics, Grounding): NAACL 2021

Senior Area Chair: AAAI 2021

Senior Area Chair (Machine Learning): EMNLP 2020

Senior Area Chair (Sentence Semantics): ACL 2020

Program Co-Chair: CoNLL 2019

Senior Program Committee Member: AAAI 2020

Area Chair (Semantics): EMNLP 2019

Area Chair (Summarization): NAACL 2019

Area Chair (Discourse, Dialogue, Summarization, Generation, Multimodal NLP): EMNLP 2018

Tutorial Chair: NAACL 2018

Area Chair (Vision, Robots, and Grounding): ACL 2017

Area Chair (Machine Learning): EMNLP 2017

Demo Chair: ACL 2017

Tutorial Chair: NAACL 2016

Area Chair: NAACL 2016

Program Committee Member / Reviewer:

Conferences: EMNLP (best reviewer award, 2012), NAACL (best reviewer award, 2018, 2015), ACL, NIPS, ICLR, IJCAI, EACL, COLING (outstanding reviewer award, 2018), *SEM, IJCNLP, ICON

Journals: TACL, TPAMI, TALIP

Workshops: ACL Workshop of Women in Natural Language Processing (2017), ACL Workshop on Representation Learning for NLP (2017), EACL Workshop on Ethics in Natural Language Processing (2017), NAACL Multilingual and Crosslingual Methods in NLP (2016), NAACL Human-Computer Question Answering (2016), ACL Evaluating Vector-Space Representations for NLP (2016), NAACL Vector Space Modeling for NLP (2015)

University Research Proposals: ORAU

Organizer: SpLU-RoboNLP Joint Workshop at NAACL 2019, CVPR 2019 Workshop on Conceptual Captions, NLP/ML Colloquium Series at UNC, Language Grounding for Robotics at ACL 2017, Midwest Speech and Language Days 2015

Committee Member: Graduate (PhD) Admissions Committee, EECS, UC Berkeley

Panel Member: National Science Foundation (NSF) Review Panels

Software and Datasets: Available as links with corresponding paper in Publications/Code/Data.