| Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work? Y Pruksachatkun, J Phang, H Liu, PM Htut, X Zhang, RY Pang, C Vania, ... Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 279 | 2020 |
| Self-Rewarding Language Models W Yuan, RY Pang, K Cho, S Sukhbaatar, J Xu, J Weston arXiv preprint arXiv:2401.10020, 2024 | 103 | 2024 |
| Text Generation by Learning from Demonstrations RY Pang, H He International Conference on Learning Representations 2021, 2021 | 79 | 2021 |
| QuALITY: Question Answering with Long Input Texts, Yes! RY Pang, A Parrish, N Joshi, N Nangia, J Phang, A Chen, V Padmakumar, ... Proceedings of the 2022 Conference of the North American Chapter of the …, 2022 | 68 | 2022 |
| Consistency of a Recurrent Language Model With Respect to Incomplete Decoding S Welleck, I Kulikov, J Kim, RY Pang, K Cho Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 63 | 2020 |
| ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation L Tu, RY Pang, S Wiseman, K Gimpel Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 52 | 2020 |
| Token Dropping for Efficient BERT Pretraining L Hou, RY Pang, T Zhou, Y Wu, X Song, X Song, D Zhou Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 33 | 2022 |
| Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer RY Pang, K Gimpel Proceedings of the 3rd Workshop on Neural Generation and Translation, 138–147, 2019 | 32 | 2019 |
| SQuALITY: Building a Long-Document Summarization Dataset the Hard Way A Wang, RY Pang, A Chen, J Phang, SR Bowman Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 28 | 2022 |
| Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples A Saparov, RY Pang, V Padmakumar, N Joshi, SM Kazemi, N Kim, H He Advances in Neural Information Processing Systems 2023, 2023 | 26 | 2023 |
| GPQA: A Graduate-Level Google-Proof Q&A Benchmark D Rein, BL Hou, AC Stickland, J Petty, RY Pang, J Dirani, J Michael, ... arXiv preprint arXiv:2311.12022, 2023 | 25 | 2023 |
| What Do NLP Researchers Believe? Results of the NLP Community Metasurvey J Michael, A Holtzman, A Parrish, A Mueller, A Wang, A Chen, D Madaan, ... Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 25* | 2023 |
| Comparing Test Sets with Item Response Theory C Vania, PM Htut, W Huang, D Mungra, RY Pang, J Phang, H Liu, K Cho, ... Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 24 | 2021 |
| AgreeSum: Agreement-Oriented Multi-Document Summarization RY Pang, AD Lelkes, VQ Tran, C Yu Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 …, 2021 | 17 | 2021 |
| The Daunting Task of Real-World Textual Style Transfer Auto-Evaluation RY Pang arXiv preprint arXiv:1910.03747, 2019 | 17* | 2019 |
| Improving Joint Training of Inference Networks and Structured Prediction Energy Networks L Tu, RY Pang, K Gimpel Proceedings of the 4th Workshop on Structured Prediction for NLP, 62–73, 2020 | 13 | 2020 |
| Reward Gaming in Conditional Text Generation RY Pang, V Padmakumar, T Sellam, AP Parikh, H He Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 9 | 2023 |
| Extrapolative Controlled Sequence Generation via Iterative Refinement V Padmakumar, RY Pang, H He, AP Parikh Proceedings of the 40th International Conference on Machine Learning, 2023 | 8 | 2023 |
| Iterative Reasoning Preference Optimization RY Pang, W Yuan, K Cho, H He, S Sukhbaatar, J Weston arXiv preprint arXiv:2404.19733, 2024 | 4 | 2024 |
| Amortized Noisy Channel Neural Machine Translation RY Pang, H He, K Cho Proceedings of the 15th International Conference on Natural Language …, 2022 | 4 | 2022 |
He HeNew York University在 cs.nyu.edu 的电子邮件经过验证
