Cheng-Yu Hsieh

According to our database, Cheng-Yu Hsieh authored at least 32 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions.

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

CoRR, 2024

DataComp-LM: In search of the next generation of training sets for language models.

Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar 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

CoRR, 2024

The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better.

Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna

CoRR, 2024

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity.

Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Kumar Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps.

Yung-Sung Chuang, Linlu Qiu, Cheng-Yu Hsieh, Ranjay Krishna, Yoon Kim, James R. Glass

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning.

Abhinav Bandari, Lu Yin, Cheng-Yu Hsieh, Ajay Jaiswal, Tianlong Chen, Li Shen, Ranjay Krishna, Shiwei Liu

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization.

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

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity.

Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Mykola Pechenizkiy, Yi Liang, Zhangyang Wang, Shiwei Liu

CoRR, 2023

Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models.

Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister

CoRR, 2023

SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality.

Cheng-Yu Hsieh, Jieyu Zhang, Zixian Ma, Aniruddha Kembhavi, Ranjay Krishna

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes.

Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming.

Cheng-Yu Hsieh, Jieyu Zhang, Alexander J. Ratner

Proc. VLDB Endow., 2022

A linear-time algorithm for weighted paired-domination on block graphs.

Ching-Chi Lin, Cheng-Yu Hsieh, Ta-Yu Mu

J. Comb. Optim., 2022

A Survey on Programmatic Weak Supervision.

Jieyu Zhang, Cheng-Yu Hsieh, Yue Yu, Chao Zhang, Alexander Ratner

CoRR, 2022

Understanding Programmatic Weak Supervision via Source-aware Influence Function.

Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander J. Ratner

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Summit-assisted Evolutionary Multitasking.

Cheng-Yu Hsieh, Rung-Tzuo Liaw

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

2021

Active Refinement for Multi-Label Learning: A Pseudo-Label Approach.

Cheng-Yu Hsieh, Wei-I Lin, Miao Xu, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama

CoRR, 2021

Evaluations and Methods for Explanation through Robustness Analysis.

Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Kumar Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Computing Urban Fabric of a Historical Town.

Naai-Jung Shih, Cheng-Yu Hsieh, Yi Chen, Pei-Huang Diao

Proceedings of 35th International Conference on Computers and Their Applications, 2020

2019

How Sensitive are Sensitivity-Based Explanations?

Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar

CoRR, 2019

On the (In)fidelity and Sensitivity of Explanations.

Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Automatic Bridge Bidding Using Deep Reinforcement Learning.

Chih-Kuan Yeh, Cheng-Yu Hsieh, Hsuan-Tien Lin

IEEE Trans. Games, 2018

A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning.

Cheng-Yu Hsieh, Yi-An Lin, Hsuan-Tien Lin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016

A Linear-Time Algorithm for the Weighted Paired-Domination Problem on Block Graphs.

Ching-Chi Lin, Cheng-Yu Hsieh

CoRR, 2016

2013

Efficient Video Stream Monitoring for Near-Duplicate Detection and Localization in a Large-Scale Repository.

Chih-Yi Chiu, Tsung-Han Tsai, Guei-Wun Han, Cheng-Yu Hsieh, Sheng-Yang Li

ACM Trans. Inf. Syst., 2013

Efficient video segment matching for detecting temporal-based video copies.

Chih-Yi Chiu, Tsung-Han Tsai, Cheng-Yu Hsieh

Neurocomputing, 2013

Egg Pair - A hearing game for the visually impaired people using RFID.

Yi-Chia Lee, Chia-Yu Yao, Cheng-Yu Hsieh, Jau-Yi Wu, Yi-Hsuan Hsieh, Chien-Hsiung Chen, Rung-Huei Liang, Ya-Shu Chen

Proceedings of the IEEE International Symposium on Consumer Electronics, 2013

2012

Video Query Reformulation for Near-Duplicate Detection.

Chih-Yi Chiu, Sheng-Yang Li, Cheng-Yu Hsieh

IEEE Trans. Inf. Forensics Secur., 2012

Scalable near-duplicate video stream monitoring.

Chih-Yi Chiu, Tsung-Han Tsai, Cheng-Yu Hsieh

Proceedings of the International Symposium on Intelligent Signal Processing and Communications Systems, 2012

2011

Design and implementation of dynamic charging plan for IMS-based multicast services.

Sok-Ian Sou, Cheng-Yu Hsieh, Fen-Yen Lee, Yu-Fu Lin, Jeu-Yih Jeng, Chien-Wei Cheng

Proceedings of the 13th Asia-Pacific Network Operations and Management Symposium, 2011

2007

All-optical multicast routing in sparse splitting WDM networks.

Cheng-Yu Hsieh, Wanjiun Liao

IEEE J. Sel. Areas Commun., 2007

2003

All Optical Multicast Routing in Sparse-Splitting Optical Networks.

Cheng-Yu Hsieh, Wanjiun Liao

Proceedings of the 28th Annual IEEE Conference on Local Computer Networks (LCN 2003), 2003