| Pre-Training BERT on Domain Resources for Short Answer Grading C Sung, T Dhamecha, S Saha, T Ma, V Reddy, R Arora EMNLP 2019, 2019 | 126 | 2019 |
| Bootstrapping for numerical open ie S Saha, H Pal, Mausam ACL 2017, 2017 | 119 | 2017 |
| Open information extraction from conjunctive sentences S Saha, Mausam COLING 2018, 2018 | 114 | 2018 |
| PRover: Proof Generation for Interpretable Reasoning over Rules S Saha, S Ghosh, S Srivastava, M Bansal EMNLP 2020, 2020 | 81 | 2020 |
| Sentence level or token level features for automatic short answer grading?: Use both S Saha, TI Dhamecha, S Marvaniya, R Sindhgatta, B Sengupta AIED 2018, 2018 | 74 | 2018 |
| ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning S Saha, P Yadav, L Bauer, M Bansal EMNLP 2021, 2021 | 48 | 2021 |
| ConjNLI: Natural Language Inference Over Conjunctive Sentences S Saha, Y Nie, M Bansal EMNLP 2020, 2020 | 38 | 2020 |
| Reconcile: Round-table conference improves reasoning via consensus among diverse llms JCY Chen, S Saha, M Bansal ACL 2024, 2023 | 36 | 2023 |
| Branch-solve-merge improves large language model evaluation and generation S Saha, O Levy, A Celikyilmaz, M Bansal, J Weston, X Li NAACL 2024, 2023 | 34 | 2023 |
| Creating scoring rubric from representative student answers for improved short answer grading S Marvaniya, S Saha, TI Dhamecha, P Foltz, R Sindhgatta, B Sengupta CIKM 2018, 2018 | 32 | 2018 |
| Can Language Models Teach? Teacher Explanations Improve Student Performance via Personalization S Saha, P Hase, M Bansal NeurIPS 2023, 2023 | 29* | 2023 |
| ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness A Prasad, S Saha, X Zhou, M Bansal EMNLP 2023, 2023 | 27 | 2023 |
| multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning S Saha, P Yadav, M Bansal NAACL 2021, 2021 | 27 | 2021 |
| Summarization programs: Interpretable abstractive summarization with neural modular trees S Saha, S Zhang, P Hase, M Bansal ICLR 2023, 2022 | 18 | 2022 |
| Joint multi-domain learning for automatic short answer grading S Saha, TI Dhamecha, S Marvaniya, P Foltz, R Sindhgatta, B Sengupta arXiv preprint arXiv:1902.09183, 2019 | 13 | 2019 |
| Are Hard Examples also Harder to Explain? A Study with Human and Model-Generated Explanations S Saha, P Hase, N Rajani, M Bansal EMNLP 2022, 2022 | 11 | 2022 |
| Balancing human efforts and performance of student response analyzer in dialog-based tutors TI Dhamecha, S Marvaniya, S Saha, R Sindhgatta, B Sengupta AIED 2018, 2018 | 11 | 2018 |
| Explanation Graph Generation via Pre-trained Language Models: An Empirical Study with Contrastive Learning S Saha, P Yadav, M Bansal ACL 2022, 2022 | 8 | 2022 |
| MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generation S Saha, XV Yu, M Bansal, R Pasunuru, A Celikyilmaz ACL 2023, 2023 | 6 | 2023 |
| Learning Outcomes and Their Relatedness in a Medical Curriculum S Mondal, T Dhamecha, S Godbole, S Pathak, R Mendoza, ... ACL-BEA 2019, 2019 | 4 | 2019 |
Mohit BansalParker Distinguished Professor, Computer Science, UNC Chapel HillVerified email at cs.unc.edu
