Cheng-Yu Hsieh

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 28

Top Topics

Top Venues

Proc. VLDB Endow.

Publications

Yung-Sung Chuang, Linlu Qiu, Cheng-Yu Hsieh, Ranjay Krishna, Yoon Kim, James R. Glass
Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps. CoRR (2024)
Yu-Guan Hsieh, Cheng-Yu Hsieh, Shih-Ying Yeh, Louis Béthune, Hadipour Ansari, Pavan Kumar Anasosalu Vasu, Chun-Liang Li, Ranjay Krishna, Oncel Tuzel, Marco Cuturi
Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions. CoRR (2024)
Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better. CoRR (2024)
Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar
DataComp-LM: In search of the next generation of training sets for language models. CoRR (2024)
Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James R. Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization. CoRR (2024)
Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James R. Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization. ACL (Findings) (2024)
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. ACL (Findings) (2023)
Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models. CoRR (2023)
Cheng-Yu Hsieh, Jieyu Zhang, Zixian Ma, Aniruddha Kembhavi, Ranjay Krishna
SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality. NeurIPS (2023)
Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Mykola Pechenizkiy, Yi Liang, Zhangyang Wang, Shiwei Liu
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. CoRR (2023)
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. CoRR (2023)
Cheng-Yu Hsieh, Jieyu Zhang, Zixian Ma, Aniruddha Kembhavi, Ranjay Krishna
SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality. CoRR (2023)
Cheng-Yu Hsieh, Jieyu Zhang, Alexander Ratner
Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming. CoRR (2022)
Cheng-Yu Hsieh, Rung-Tzuo Liaw
Summit-assisted Evolutionary Multitasking. CEC (2022)
Cheng-Yu Hsieh, Jieyu Zhang, Alexander J. Ratner
Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming. Proc. VLDB Endow. 15 (13) (2022)
Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander J. Ratner
Understanding Programmatic Weak Supervision via Source-aware Influence Function. NeurIPS (2022)
Ching-Chi Lin, Cheng-Yu Hsieh, Ta-Yu Mu
A linear-time algorithm for weighted paired-domination on block graphs. J. Comb. Optim. 44 (1) (2022)
Jieyu Zhang, Cheng-Yu Hsieh, Yue Yu, Chao Zhang, Alexander Ratner
A Survey on Programmatic Weak Supervision. CoRR (2022)
Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander Ratner
Understanding Programmatic Weak Supervision via Source-aware Influence Function. CoRR (2022)
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Kumar Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
Evaluations and Methods for Explanation through Robustness Analysis. ICLR (2021)
Cheng-Yu Hsieh, Wei-I Lin, Miao Xu, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
Active Refinement for Multi-Label Learning: A Pseudo-Label Approach. CoRR (2021)
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
Evaluations and Methods for Explanation through Robustness Analysis. CoRR (2020)
Naai-Jung Shih, Cheng-Yu Hsieh, Yi Chen, Pei-Huang Diao
Computing Urban Fabric of a Historical Town. CATA (2020)
Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar
On the (In)fidelity and Sensitivity of Explanations. NeurIPS (2019)
Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar
How Sensitive are Sensitivity-Based Explanations? CoRR (2019)
Cheng-Yu Hsieh, Yi-An Lin, Hsuan-Tien Lin
A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning. AAAI (2018)
Chih-Kuan Yeh, Cheng-Yu Hsieh, Hsuan-Tien Lin
Automatic Bridge Bidding Using Deep Reinforcement Learning. IEEE Trans. Games 10 (4) (2018)
Ching-Chi Lin, Cheng-Yu Hsieh
A Linear-Time Algorithm for the Weighted Paired-Domination Problem on Block Graphs. CoRR (2016)
Chih-Yi Chiu, Tsung-Han Tsai, Guei-Wun Han, Cheng-Yu Hsieh, Sheng-Yang Li
Efficient Video Stream Monitoring for Near-Duplicate Detection and Localization in a Large-Scale Repository. ACM Trans. Inf. Syst. 31 (4) (2013)
Chih-Yi Chiu, Tsung-Han Tsai, Cheng-Yu Hsieh
Efficient video segment matching for detecting temporal-based video copies. Neurocomputing 105 (2013)
Yi-Chia Lee, Chia-Yu Yao, Cheng-Yu Hsieh, Jau-Yi Wu, Yi-Hsuan Hsieh, Chien-Hsiung Chen, Rung-Huei Liang, Ya-Shu Chen
Egg Pair - A hearing game for the visually impaired people using RFID. ISCE (2013)
Chih-Yi Chiu, Sheng-Yang Li, Cheng-Yu Hsieh
Video Query Reformulation for Near-Duplicate Detection. IEEE Trans. Inf. Forensics Secur. 7 (5) (2012)
Chih-Yi Chiu, Tsung-Han Tsai, Cheng-Yu Hsieh
Scalable near-duplicate video stream monitoring. ISPACS (2012)
Sok-Ian Sou, Cheng-Yu Hsieh, Fen-Yen Lee, Yu-Fu Lin, Jeu-Yih Jeng, Chien-Wei Cheng
Design and implementation of dynamic charging plan for IMS-based multicast services. APNOMS (2011)
Cheng-Yu Hsieh, Wanjiun Liao
All-optical multicast routing in sparse splitting WDM networks. IEEE J. Sel. Areas Commun. 25 (S-6) (2007)
Cheng-Yu Hsieh, Wanjiun Liao
All Optical Multicast Routing in Sparse-Splitting Optical Networks. LCN (2003)