עקוב אחר
Cheng-Yu Hsieh
Cheng-Yu Hsieh
Ph.D. student, University of Washington
כתובת אימייל מאומתת בדומיין cs.washington.edu - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
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
5172019
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, ...‏
arXiv preprint arXiv:2305.02301, 2023‏
4522023
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
1152023
Datacomp-lm: In search of the next generation of training sets for language models‏
J Li, A Fang, G Smyrnis, M Ivgi, M Jordan, SY Gadre, H Bansal, E Guha, ...‏
Advances in Neural Information Processing Systems 37, 14200-14282, 2025‏
93*2025
A survey on programmatic weak supervision‏
J Zhang, CY Hsieh, Y Yu, C Zhang, A Ratner‏
arXiv preprint arXiv:2202.05433, 2022‏
892022
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
652023
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
652021
Automatic bridge bidding using deep reinforcement learning‏
CK Yeh, CY Hsieh, HT Lin‏
IEEE Transactions on Games 10 (4), 365-377, 2018‏
602018
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
562023
How sensitive are sensitivity-based explanations‏
CK Yeh, CY Hsieh, AS Suggala, D Inouye, P Ravikumar‏
arXiv preprint arXiv:1901.09392, 52, 2019‏
252019
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
arXiv preprint arXiv:2407.07071, 2024‏
202024
A deep model with local surrogate loss for general cost-sensitive multi-label learning‏
CY Hsieh, YA Lin, HT Lin‏
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018‏
172018
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
162022
Found in the middle: Calibrating positional attention bias improves long context utilization‏
CY Hsieh, YS Chuang, CL Li, Z Wang, LT Le, A Kumar, J Glass, A Ratner, ...‏
arXiv preprint arXiv:2406.16008, 2024‏
142024
Understanding Programmatic Weak Supervision via Source-aware Influence Function‏
J Zhang, H Wang, CY Hsieh, A Ratner‏
Advances in Neural Information Processing Systems, 2022‏
132022
A pseudo-label method for coarse-to-fine multi-label learning with limited supervision‏
CY Hsieh, M Xu, G Niu, HT Lin, M Sugiyama‏
Learning from Limited Labeled Data Workshop @ ICLR '19, 2019‏
92019
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, ...‏
arXiv preprint arXiv:2412.04468, 2024‏
72024
The unmet promise of synthetic training images: Using retrieved real images performs better‏
S Geng, CY Hsieh, V Ramanujan, M Wallingford, CL Li, PWW Koh, ...‏
Advances in Neural Information Processing Systems 37, 7902-7929, 2025‏
32025
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
arXiv preprint arXiv:2410.07461, 2024‏
32024
The hard positive truth about vision-language compositionality‏
A Kamath, CY Hsieh, KW Chang, R Krishna‏
European Conference on Computer Vision, 37-54, 2024‏
32024
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מאמרים 1–20