Research
Papers are roughly grouped by topic below. For a full list, see my Google Scholar or Semantic Scholar.
LLM-as-a-Judge and Generative Reward Models
J1: Incentivizing Thinking in LLM-as-a-Judge via Reinforcement Learning
Chenxi Whitehouse, Tianlu Wang, Ping Yu, Xian Li, Jason Weston, Ilia Kulikov, Swarnadeep Saha
Pre-print on arXiv, 2025
[paper] [tweet] [Long]Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
Swarnadeep Saha, Xian Li, Marjan Ghazvininejad, Jason Weston, Tianlu Wang
International Conference on Machine Learning (ICML), 2025
[paper] [tweet] [Long]Branch-Solve-Merge Improves Large Language Model Evaluation and Generation
Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, Mohit Bansal, Jason Weston, and Xian Li
Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024
[paper] [tweet] [Long]
Planning and Reasoning in Multi-Agent Systems
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
International Conference on Learning Representations (ICLR) 2025
[paper] [code] [tweet] [Long]MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning
Justin Chih-Yao Chen, Archiki Prasad, Swarnadeep Saha, Elias Stengel-Eskin, Mohit Bansal
Pre-print on arXiv, 2024
[paper] [code] [tweet] [Long]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
International Conference on Machine Learning (ICML), 2024
[paper] [code] [tweet] [Long]ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs
Justin Chih-Yao Chen, Swarnadeep Saha, and Mohit Bansal
Annual Meeting of the Association for Computational Linguistics (ACL), 2024
[paper] [code] [tweet] [Long]Can Language Models Teach Weaker Agents? Teacher Explanations Improve Students via Personalization
Swarnadeep Saha, Peter Hase, and Mohit Bansal
Neural Information Processing Systems (NeurIPS), 2023
[paper] [code] [tweet] [Long] [Poster]ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness
Archiki Prasad, Swarnadeep Saha, Xiang Zhou, and Mohit Bansal
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023
[paper] [code] [tweet] [Long] [Poster]
Attributable Generative Reasoning
Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees
Swarnadeep Saha, Shiyue Zhang, Peter Hase, and Mohit Bansal
International Conference on Learning Representations (ICLR), 2023
[paper] [code] [tweet] [Long] [Poster]MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generation
Swarnadeep Saha, Xinyan Velocity Yu, Mohit Bansal, Ramakanth Pasunuru, and Asli Celikyilmaz
Annual Meeting of the Association for Computational Linguistics (Findings of ACL), 2023
[paper] [tweet] [Long] [Poster]
Structured Reasoning over Implicit Knowledge
Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning
Swarnadeep Saha, Prateek Yadav, and Mohit Bansal
Annual Meeting of the Association for Computational Linguistics (ACL), 2022
[paper] [code] [tweet] [Long] [Poster]ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning
Swarnadeep Saha, Prateek Yadav, Lisa Bauer, and Mohit Bansal
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
[paper] [data/code] [website] [tweet] [Long] [Oral]
Deductive Reasoning
multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning
Swarnadeep Saha, Prateek Yadav, and Mohit Bansal
Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2021
[paper] [code] [tweet] [Long] [Oral]PRover: Proof Generation for Interpretable Reasoning over Rules
Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, and Mohit Bansal
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
[paper] [code] [tweet] [Long] [Oral]
Additional Topics (During PhD)
Are Hard Examples also Harder to Explain? A Study with Human and Model-Generated Explanations
Swarnadeep Saha, Peter Hase, Nazneen Rajani, and Mohit Bansal
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
[paper] [data] [tweet] [Short] [Oral]ConjNLI: Natural Language Inference over Conjunctive Sentences
Swarnadeep Saha, Yixin Nie, and Mohit Bansal
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
[paper] [data/code] [tweet] [Long] [Poster]
Open Information Extraction
Open Information Extraction from Conjunctive Sentences
Swarnadeep Saha, and Mausam
27th International Conference on Computational Linguistics (COLING), 2018
[paper] [code] [Long] [Oral]Bootstrapping for Numerical Open IE
Swarnadeep Saha, Harinder Pal, and Mausam
55th Annual Meeting of the Association for Computational Linguistics (ACL), 2017
[paper] [code] [Short] [Poster]
Educational NLP
Pre-Training BERT on Domain Resources for Short Answer Grading
Chul Sung, Tejas Dhamecha, Swarnadeep Saha, Tengfei Ma, Vinay Reddy, and Rishi Arora
Conference on Empirical Methods in Natural Language Processing (EMNLP-IJCNLP), 2019
[paper] [Short] [Poster]Aligning Learning Objectives to Learning Resources: A Lexico-Semantic Spatial Approach
Swarnadeep Saha, Malolan Chetlur, Tejas Indulal Dhamecha, W M Gayathri K Wijayarathna, Red Mendoza, Paul Gagnon, Nabil Zary, and Shantanu Godbole
28th International Joint Conference on Artificial Intelligence (IJCAI), 2019
[paper] [Long] [Oral]Creating Scoring Rubric from Representative Student Answers for Improved Short Answer Grading
Smit Marvaniya, Swarnadeep Saha, Tejas I. Dhamecha, Peter Foltz, Renuka Sindhgatta, and Bikram Sengupta
27th ACM International Conference on Information and Knowledge Management (CIKM), 2018
[paper] [Long] [Oral]