| HoVer: A dataset for many-hop fact extraction and claim verification Y Jiang, S Bordia, Z Zhong, C Dognin, M Singh, M Bansal 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020 | 108 | 2020 |
| Avoiding reasoning shortcuts: Adversarial evaluation, training, and model development for multi-hop QA Y Jiang, M Bansal ACL 2019, 2019 | 102 | 2019 |
| Self-assembling modular networks for interpretable multi-hop reasoning Y Jiang, M Bansal 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019), 2019 | 97 | 2019 |
| Explore, propose, and assemble: An interpretable model for multi-hop reading comprehension Y Jiang, N Joshi, YC Chen, M Bansal ACL 2019, 2019 | 55 | 2019 |
| Closed-book training to improve summarization encoder memory Y Jiang, M Bansal 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018), 2018 | 37 | 2018 |
| Inducing Transformer's Compositional Generalization Ability via Auxiliary Sequence Prediction Tasks Y Jiang, M Bansal 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), 2021 | 22 | 2021 |
| Enriching transformers with structured tensor-product representations for abstractive summarization Y Jiang, A Celikyilmaz, P Smolensky, P Soulos, S Rao, H Palangi, ... NAACL 2021, 2021 | 15 | 2021 |
| Mutual exclusivity training and primitive augmentation to induce compositionality Y Jiang, X Zhou, M Bansal 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), 2022 | 5 | 2022 |
| Structural biases for improving transformers on translation into morphologically rich languages P Soulos, S Rao, C Smith, E Rosen, A Celikyilmaz, RT McCoy, Y Jiang, ... 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021), 2021 | 3 | 2021 |
| Machine Learning Systems and Methods for Many-Hop Fact Extraction and Claim Verification Y Jiang, S Bordia, Z Zhong, C Dognin, MK Singh, M Bansal US Patent App. 17/534,899, 2022 | 2 | 2022 |
| Learning and analyzing generation order for undirected sequence models Y Jiang, M Bansal 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), 2021 | 2 | 2021 |
| Augmenting Neural Encoder-Decoder Model for Natural Language Generation Tasks Y Jiang University of North Carolina at Chapel Hill, 2018 | | 2018 |
Mohit BansalParker Distinguished Professor, Computer Science, UNC Chapel HillBestätigte E-Mail-Adresse bei cs.unc.edu
