| Rewardbench: Evaluating reward models for language modeling N Lambert, V Pyatkin, J Morrison, LJ Miranda, BY Lin, K Chandu, N Dziri, ... NAACL 2025, 2024 | 492* | 2024 |
| Dolma: An open corpus of three trillion tokens for language model pretraining research L Soldaini, R Kinney, A Bhagia, D Schwenk, D Atkinson, R Authur, ... ACL 2024 (Best Resource Paper Award), 2024 | 433* | 2024 |
| Wildteaming at scale: From in-the-wild jailbreaks to (adversarially) safer language models L Jiang, K Rao, S Han, A Ettinger, F Brahman, S Kumar, N Mireshghallah, ... Advances in Neural Information Processing Systems 37, 47094-47165, 2024 | 191* | 2024 |
| Do all languages cost the same? tokenization in the era of commercial language models O Ahia, S Kumar, H Gonen, J Kasai, DR Mortensen, NA Smith, Y Tsvetkov EMNLP 2023, 2023 | 145 | 2023 |
| Ssd-lm: Semi-autoregressive simplex-based diffusion language model for text generation and modular control X Han, S Kumar, Y Tsvetkov ACL 2023, 2022 | 142 | 2022 |
| Language generation models can cause harm: So what can we do about it? an actionable survey S Kumar, V Balachandran, L Njoo, A Anastasopoulos, Y Tsvetkov EACL 2023, 2022 | 121 | 2022 |
| Minding language models'(lack of) theory of mind: A plug-and-play multi-character belief tracker M Sclar, S Kumar, P West, A Suhr, Y Choi, Y Tsvetkov ACL 2023 (Outstanding Paper Award), 2023 | 119 | 2023 |
| Earth mover's distance pooling over siamese LSTMs for automatic short answer grading S Kumar, S Chakrabarti, S Roy | 106 | 2017 |
| Controlled text generation as continuous optimization with multiple constraints S Kumar, E Malmi, A Severyn, Y Tsvetkov Advances in Neural Information Processing Systems 34, 14542-14554, 2021 | 102 | 2021 |
| Von mises-fisher loss for training sequence to sequence models with continuous outputs S Kumar, Y Tsvetkov ICLR 2019, 2018 | 91 | 2018 |
| Gradient-based constrained sampling from language models S Kumar, B Paria, Y Tsvetkov EMNLP 2022, 2022 | 81* | 2022 |
| The art of saying no: Contextual noncompliance in language models F Brahman, S Kumar, V Balachandran, P Dasigi, V Pyatkin, ... Advances in Neural Information Processing Systems 37, 49706-49748, 2024 | 76 | 2024 |
| On the blind spots of model-based evaluation metrics for text generation T He, J Zhang, T Wang, S Kumar, K Cho, J Glass, Y Tsvetkov ACL 2023, 2022 | 53 | 2022 |
| Assessing language model deployment with risk cards L Derczynski, HR Kirk, V Balachandran, S Kumar, Y Tsvetkov, MR Leiser, ... arXiv preprint arXiv:2303.18190, 2023 | 45 | 2023 |
| Machine translation into low-resource language varieties S Kumar, A Anastasopoulos, S Wintner, Y Tsvetkov ACL 2021, 2021 | 44 | 2021 |
| Topics to avoid: Demoting latent confounds in text classification S Kumar, S Wintner, NA Smith, Y Tsvetkov EMNLP 2019, 2019 | 42 | 2019 |
| Hybrid preferences: Learning to route instances for human vs. AI feedback LJV Miranda, Y Wang, Y Elazar, S Kumar, V Pyatkin, F Brahman, ... ACL 2025, 2024 | 23* | 2024 |
| Magnet: Improving the multilingual fairness of language models with adaptive gradient-based tokenization O Ahia, S Kumar, H Gonen, V Hofmann, T Limisiewicz, Y Tsvetkov, ... Advances in Neural Information Processing Systems 37, 47790-47814, 2024 | 22 | 2024 |
| Neural abstractive summarization with structural attention T Chowdhury, S Kumar, T Chakraborty arXiv preprint arXiv:2004.09739, 2020 | 21 | 2020 |
| Referee: Reference-free sentence summarization with sharper controllability through symbolic knowledge distillation M Sclar, P West, S Kumar, Y Tsvetkov, Y Choi EMNLP 2022, 2022 | 20 | 2022 |
Yulia TsvetkovUniversity of WashingtonVerified email at cs.washington.edu
