| HoVer: A dataset for many-hop fact extraction and claim verification Y Jiang, S Bordia, Z Zhong, C Dognin, M Singh, M Bansal arXiv preprint arXiv:2011.03088, 2020 | 105 | 2020 |
| Avoiding reasoning shortcuts: Adversarial evaluation, training, and model development for multi-hop QA Y Jiang, M Bansal arXiv preprint arXiv:1906.07132, 2019 | 101 | 2019 |
| Self-assembling modular networks for interpretable multi-hop reasoning Y Jiang, M Bansal arXiv preprint arXiv:1909.05803, 2019 | 97 | 2019 |
| Explore, propose, and assemble: An interpretable model for multi-hop reading comprehension Y Jiang, N Joshi, YC Chen, M Bansal arXiv preprint arXiv:1906.05210, 2019 | 55 | 2019 |
| Closed-book training to improve summarization encoder memory Y Jiang, M Bansal arXiv preprint arXiv:1809.04585, 2018 | 37 | 2018 |
| Inducing Transformer's Compositional Generalization Ability via Auxiliary Sequence Prediction Tasks Y Jiang, M Bansal arXiv preprint arXiv:2109.15256, 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, ... arXiv preprint arXiv:2106.01317, 2021 | 15 | 2021 |
| Mutual exclusivity training and primitive augmentation to induce compositionality Y Jiang, X Zhou, M Bansal arXiv preprint arXiv:2211.15578, 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, ... arXiv preprint arXiv:2208.06061, 2022 | 3 | 2022 |
| 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 arXiv preprint arXiv:2112.09097, 2021 | 2 | 2021 |
| Augmenting Neural Encoder-Decoder Model for Natural Language Generation Tasks Y Jiang | | 2018 |
Mohit BansalParker Distinguished Professor, Computer Science, UNC Chapel Hill在 cs.unc.edu 的电子邮件经过验证
