Rakesh R Menon

I am a PhD candidate in the UNC-NLP lab advised by Dr. Shashank Srivastava. My research interests lie in the intersection of machine learning and natural language processing. Currently, my research focuses on using language to supervise and interpret machine learning models.

Publications

DiScErN: Decoding Systematic Errors in Natural Language for Text Classifiers
Rakesh R Menon, Shashank Srivastava
Proceedings of Empirical Methods in Natural Language Processing. EMNLP 2024
[PDF] [arXiv] [Code]
SocialGaze: Improving the Integration of Human Social Norms in Large Language Models
Anvesh Rao Vijjini*, Rakesh R Menon*, Shashank Srivastava, Snigdha Chaturvedi
Findings of Empirical Methods in Natural Language Processing. EMNLP 2024
6th Workshop on Narrative Understanding. EMNLP 2024
[PDF] [arXiv] [Code]
MaNtLE: Model-agnostic Natural Language Explainer
Rakesh R Menon, Kerem Zaman, Shashank Srivastava
Proceedings of Empirical Methods in Natural Language Processing. EMNLP 2023
[PDF] [arXiv] [Code]
Pragmatic Reasoning Unlocks Quantifier Semantics for Foundation Models
Yiyuan Li, Rakesh R Menon, Sayan Ghosh, Shashank Srivastava
Proceedings of Empirical Methods in Natural Language Processing. EMNLP 2023
Oral Presentation
[PDF] [arXiv] [Code]
Leveraging Multiple Teachers for Test-Time Adaptation of Language-Guided Classifiers
Kangda Wei, Sayan Ghosh, Rakesh R Menon, Shashank Srivastava
Findings of Empirical Methods in Natural Language Processing. EMNLP 2023
[PDF] [arXiv] [Code]
DelucionQA: Detecting Hallucinations in Domain-specific Question Answering
Mobashir Sadat, Zhengyu Zhou, Lukas Lange, Jun Araki, Arsalan Gundroo, Bingqing Wang, Rakesh R Menon, Md Rizwan Parvez, Zhe Feng
Findings of Empirical Methods in Natural Language Processing. EMNLP 2023
[PDF] [arXiv] [Code]
LaSQuE: Improved Zero-Shot Classification from Explanations Through Quantifier Modeling and Curriculum Learning
Sayan Ghosh*, Rakesh R Menon*, Shashank Srivastava
Findings of the Association for Computational Linguistics. ACL 2023
Workshop on Learning with Natural Language Supervision. ACL 2022
[PDF] [arXiv]
CoAug: Combining Augmentation of Labels and Labelling Rules
Rakesh R Menon, Bingqing Wang, Jun Araki, Zhengyu Zhou, Zhe Feng, Liu Ren
Findings of the Association for Computational Linguistics. ACL 2023 (short)
[PDF] [Code]
CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations
Rakesh R Menon*, Sayan Ghosh*, Shashank Srivastava
Proceedings of the Annual Meeting of the Association for Computational Linguistics. ACL 2022
Workshop on Learning with Natural Language Supervision. ACL 2022
Spotlight Presentation
[PDF] [arXiv] [Dataset] [Code]
Improving and Simplifying Pattern Exploiting-Training
Derek Tam*, Rakesh R Menon*, Mohit Bansal, Shashank Srivastava, Colin Raffel
Proceedings of Empirical Methods in Natural Language Processing. EMNLP 2021 (short)
[PDF] [arXiv] [Code] [Talk]
[video (AI Coffee Break with Letitia)] [video (Henry AI Labs)]
MoA-Net: Self-Supervised Motion Segmentation
Pia Bideau, Rakesh R Menon, Erik Learned-Miller
“What is Optical Flow For?” Workshop. ECCV 2018
Best Paper Award Oral Presentation
[PDF] [Slides]
The Best of Both Worlds: Combining CNNs and Geometric Constraints for Hierarchical Motion Segmentation
Pia Bideau, Aruni RoyChowdhury, Rakesh R Menon, Erik Learned-Miller
IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2018.
[PDF] [Project Page] [Code] [Evaluation Code]
Prediction Error-based Transfer in Q-Ensembles
Rakesh R Menon, Balaraman Ravindran
Deep Reinforcement Learning Symposium. NeurIPS 2017.
[PDF]
Shared Learning in Ensemble Deep Q-Networks
Rakesh R Menon*, Manu Srinath Halvagal*, Balaraman Ravindran
Reinforcement Learning and Decision Making Conference. RLDM 2017.
Adaptive Learning Agents Workshop. AAMAS 2017
Oral Presentation
[PDF]