About

Dr. Mohit Bansal is the John R. & Louise S. Parker Associate Professor and the Director of the MURGe-Lab (in the 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 grounded and embodied semantics, human-like language generation and Q&A/dialogue, and interpretable and generalizable deep learning. He is a recipient of the 2020 IJCAI Early CAREER Spotlight, 2019 DARPA Director's fellowship, 2019 NSF CAREER Award, 2019 Google Focused Research Award, 2019 Microsoft Investigator Fellowship, 2018 ARO Young Investigator Award (YIP), 2017 DARPA Young Faculty Award (YFA), and several best/outstanding paper awards at ACL, CVPR, EACL, COLING, and CoNLL. His service includes ACL Executive Committee, ACM Doctoral Dissertation Award Committee, Program Co-Chair for CoNLL 2019, Senior Area Chair for several conferences, ACL Americas Sponsorship Co-Chair, and Associate/Action Editor for TACL, Computational Linguistics (CL), IEEE/ACM TASLP, and CSL journals.

Research Interests

Statistical natural language processing and machine learning, with a focus on multimodal, grounded, and embodied semantics (i.e., language with vision and speech, for robotics), human-like language generation and Q&A/dialogue, and interpretable and generalizable deep learning.

Work Experience

Computer Science department, UNC Chapel Hill (2016 — present) Associate Professor (2020-present) Assistant Professor (2016-2020) John R. & Louise S. Parker Distinguished Professorship Director, MURGe-Lab (UNC-NLP Group)
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)

Publications (+Code/Data)

• TOPIC-BASED LISTS:
  
  Generation (Summarization, Dialogue, QG, Translation, Captioning, Robotic Instruction Generation, Explanation Generation, etc.): 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.
  
  Multimodal (Images+/Videos+/Actions+Language, Grounding, RoboNLP, Navigation/Assembling, Instruction Understanding+Generation): 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.
  
  Explainability, Interpretability, Diagnosis, Adversarial Learning, Data-Augmentation: EMNLP20f, EMNLP20h, EMNLPF20a, EMNLPF20d, ACL20a, ACL20c, ACL20f, IJCAI20, AAAI20a, EMNLP19b, EMNLP19c, EMNLP19e, ACL19b, ACL19c, NAACL19a, AAAI19b, CoNLL18, NAACL18c, NAACL18d, EMNLP16a.
  
  QA: 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: EMNLP20g, EMNLPF20d, EMNLPF20e, AAAI20a, EMNLP19e, ACL19a, NAACL19b, COLING18, TACL18, ACL18a, ACL18b, NAACL18b, EMNLP17a, ACL17, CVPR17.
  
  NLU (NLI/Entailment/Next-Event Prediction, Fact Verification, Debiasing, Uncertainty, Representation Learning, Paraphrasing, Commonsense, Knowledge Graphs, Parsing, Relation Extraction, etc.): 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.: EMNLP20a, ACL20c, EMNLP18b, TACL18, WiNLP18, NAACL18c, NAACL18e, EMNLP16a, CVPR16.  
  
  
• RECENT PREPRINTS:
  

• GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models
  Archiki Prasad, Peter Hase, Xiang Zhou, Mohit Bansal.
  arXiv Preprint: 2203.07281. [pdf][code]

• DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers
  Jaemin Cho, Abhay Zala, Mohit Bansal.
  arXiv Preprint: 2202.04053. [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]

• A Proposition-Level Clustering Approach for Multi-Document Summarization
  Ori Ernst, Avi Caciularu, Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Jacob Goldberger, Ido Dagan.
  arXiv Preprint: 2112.08770. [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.
  arXiv Preprint: 2112.08637. [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]

• 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.
  arXiv Preprint: 2111.13654. [pdf][code]

• Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
  Prateek Yadav, Peter Hase, Mohit Bansal.
  arXiv Preprint: 2111.01235. [pdf][code]

• VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning
  Hao Tan, Jie Lei, Thomas Wolf, Mohit Bansal.
  arXiv Preprint: 2106.11250. [pdf][code]

• An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
  Jiaao Chen*, Derek Tam*, Colin Raffel, Mohit Bansal, Diyi Yang.
  arXiv Preprint: 2106.07499. [pdf]

• When Can Models Learn From Explanations? A Formal Framework for Understanding the Roles of Explanation Data
  Peter Hase, Mohit Bansal.
  arXiv Preprint: 2102.02201. [pdf][bib][code]

• REFEREED PUBLICATIONS:
  
  2022

• 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]

• 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]

• 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 (oral)
  Lisa Bauer and Mohit Bansal.
  Proceedings of EACL 2021. [pdf][code]

• Hidden Biases in Unreliable News Detection Datasets (oral)
  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)

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 Faculty Fellow/Scholar (Distinguished Asst./Assoc. 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:

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:

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)

Teaching

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:

Keynote, 15th International Conference on Natural Language Generation (INLG 2022)

Robustness in Sequential Data (ROSE) Workshop, CVPR 2022

Open-Domain Retrieval Under a Multi-Modal Setting (O-DRUM) 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:
Lisa Bauer (UNC, PhD) (NSF Graduate Research Fellow)
Hyounghun Kim (UNC, PhD)
Jie Lei (UNC, PhD; co-advisor: Tamara Berg) (Adobe Research Fellow)
Yixin Nie (UNC, PhD)
Darryl Hannan (UNC, PhD) (NSF Graduate Research Fellow)
Shiyue Zhang (UNC, PhD)
Xiang Zhou (UNC, PhD)
Peter Hase (UNC, PhD) (Royster Society PhD Fellow)
Yichen Jiang (UNC, PhD)
Adyasha Maharana (UNC, PhD)
Swarnadeep Saha (UNC, PhD)
Jaemin Cho (UNC, PhD)
Jialu Li (UNC, PhD)
Derek Tam (UNC, PhD)
Prateek Yadav (UNC, PhD)

Samip Dahal (UNC, BS)
Antonio Mendoza (UNC, BS)
Zineng Tang (UNC, BS)
Hanna Tischer (UNC, BS)
Abhay Zala (UNC, BS)

Past Advisees:
Ramakanth Pasunuru (UNC, PhD) (Microsoft Research PhD Fellow; Facebook PhD Fellowship Finalist) --> Research Scientist, Facebook AI
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
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

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 (2020-2023)

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.