| Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes CY Hsieh, CL Li, CK Yeh, H Nakhost, Y Fujii, A Ratner, R Krishna, CY Lee, ... Findings of the association for computational linguistics: ACL 2023, 8003-8017, 2023 | 1371 | 2023 |
| On the (In) fidelity and Sensitivity of Explanations CK Yeh, CY Hsieh, A Suggala, DI Inouye, PK Ravikumar Advances in Neural Information Processing Systems, 10965-10976, 2019 | 888 | 2019 |
| Datacomp-lm: In search of the next generation of training sets for language models J Li, A Fang, G Smyrnis, M Ivgi, M Jordan, S Gadre, H Bansal, E Guha, ... Advances in Neural Information Processing Systems 37, 14200-14282, 2024 | 594* | 2024 |
| Sugarcrepe: Fixing hackable benchmarks for vision-language compositionality CY Hsieh, J Zhang, Z Ma, A Kembhavi, R Krishna Advances in neural information processing systems 36, 31096-31116, 2023 | 341 | 2023 |
| Nvila: Efficient frontier visual language models Z Liu, L Zhu, B Shi, Z Zhang, Y Lou, S Yang, H Xi, S Cao, Y Gu, D Li, X Li, ... 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2025 | 256 | 2025 |
| Outlier weighed layerwise sparsity (owl): A missing secret sauce for pruning llms to high sparsity L Yin, Y Wu, Z Zhang, CY Hsieh, Y Wang, Y Jia, G Li, A Jaiswal, ... arXiv preprint arXiv:2310.05175, 2023 | 236 | 2023 |
| Lookback lens: Detecting and mitigating contextual hallucinations in large language models using only attention maps YS Chuang, L Qiu, CY Hsieh, R Krishna, Y Kim, J Glass Proceedings of the 2024 Conference on Empirical Methods in Natural Language …, 2024 | 213 | 2024 |
| Found in the middle: Calibrating positional attention bias improves long context utilization CY Hsieh, YS Chuang, CL Li, Z Wang, L Le, A Kumar, J Glass, A Ratner, ... Findings of the Association for Computational Linguistics: ACL 2024, 14982-14995, 2024 | 156* | 2024 |
| Tool documentation enables zero-shot tool-usage with large language models CY Hsieh, SA Chen, CL Li, Y Fujii, A Ratner, CY Lee, R Krishna, T Pfister arXiv preprint arXiv:2308.00675, 2023 | 153 | 2023 |
| A survey on programmatic weak supervision J Zhang, CY Hsieh, Y Yu, C Zhang, A Ratner arXiv preprint arXiv:2202.05433, 2022 | 146 | 2022 |
| Evaluations and Methods for Explanation through Robustness Analysis CY Hsieh, CK Yeh, X Liu, P Ravikumar, S Kim, S Kumar, CJ Hsieh International Conference on Learning Representations, 2021 | 95 | 2021 |
| Perception tokens enhance visual reasoning in multimodal language models M Bigverdi, Z Luo, CY Hsieh, E Shen, D Chen, LG Shapiro, R Krishna 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2025 | 94 | 2025 |
| Automatic bridge bidding using deep reinforcement learning CK Yeh, CY Hsieh, HT Lin IEEE Transactions on Games 10 (4), 365-377, 2018 | 75 | 2018 |
| The hard positive truth about vision-language compositionality A Kamath, CY Hsieh, KW Chang, R Krishna European Conference on Computer Vision, 37-54, 2024 | 30 | 2024 |
| The unmet promise of synthetic training images: Using retrieved real images performs better S Geng, CY Hsieh, V Ramanujan, M Wallingford, CL Li, PW Koh, ... Advances in Neural Information Processing Systems 37, 7902-7929, 2024 | 29 | 2024 |
| Datacomp-lm: In search of the next generation of training sets for language models, 2025 J Li, A Fang, G Smyrnis, M Ivgi, M Jordan, S Gadre, H Bansal, E Guha, ... URL https://arxiv. org/abs/2406.11794, 0 | 29 | |
| Is c4 dataset optimal for pruning? an investigation of calibration data for llm pruning A Bandari, L Yin, CY Hsieh, AK Jaiswal, T Chen, L Shen, R Krishna, S Liu Proceedings of the 2024 Conference on Empirical Methods in Natural Language …, 2024 | 28 | 2024 |
| How sensitive are sensitivity-based explanations CK Yeh, CY Hsieh, AS Suggala, D Inouye, P Ravikumar arXiv preprint arXiv:1901.09392, 52, 2019 | 28 | 2019 |
| Nemo: Guiding and contextualizing weak supervision for interactive data programming CY Hsieh, J Zhang, A Ratner Proceedings of the VLDB Endowment 15 (13), 4093 - 4105, 2022 | 24 | 2022 |
| Understanding Programmatic Weak Supervision via Source-aware Influence Function J Zhang, H Wang, CY Hsieh, A Ratner Advances in Neural Information Processing Systems, 2022 | 21 | 2022 |
Ranjay KrishnaUniversity of Washington, Microsoft AIVerified email at cs.washington.edu
