Yu-Neng Chuang

According to our database, Yu-Neng Chuang authored at least 48 papers between 2017 and 2026.

Collaborative distances:

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

2026

Demystifying OPD: Length Inflation and Stabilization Strategies for Large Language Models.

Feng Luo, Yu-Neng Chuang, Guanchu Wang, Zicheng Xu, Xiaotian Han, Tianyi Zhang, Vladimir Braverman

CoRR, April, 2026

Privacy-Preserving Representation Learning with Gradient Obfuscation against Attribute Inference for Recommendation.

Yu-Neng Chuang, Cheng-Te Li

ACM Trans. Knowl. Discov. Data, January, 2026

The LLM Data Auditor: A Metric-oriented Survey on Quality and Trustworthiness in Evaluating Synthetic Data.

Kaituo Zhang, Mingzhi Hu, Hoang Anh Duy Le, Fariha Kabir Torsha, Zhimeng Jiang, Minh Khai Bui, Chia-Yuan Chang, Yu-Neng Chuang, Zhen Xiong, Ying Lin, Guanchu Wang, Na Zou

CoRR, January, 2026

Context matching is not reasoning when performing generalized clinical evaluation of generative language models.

Andrew Wen, Qiuhao Lu, Yu-Neng Chuang, Guanchu Wang, Jiayi Yuan, Jiamu Zhang, Liwei Wang, Sunyang Fu, Kurt Miller, Heling Jia, Stephen Bedrick, William R. Hersh, Kirk E. Roberts, Xia (Ben) Hu, Hongfang Liu

npj Digit. Medicine, 2026

FaithLM: Towards Faithful Explanations for Large Language Models.

Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Ruixiang Tang, Shaochen Zhong, Fan Yang, Andrew Wen, Mengnan Du, Xuanting Cai, Vladimir Braverman, Xia Hu

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

2025

LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting.

Yu-Neng Chuang, Songchen Li, Jiayi Yuan, Guanchu Wang, Kwei-Herng Lai, Songyuan Sui, Leisheng Yu, Sirui Ding, Chia-Yuan Chang, Alfredo Costilla-Reyes, Daochen Zha, Xia Hu

SIGKDD Explor., December, 2025

DTS: Enhancing Large Reasoning Models via Decoding Tree Sketching.

Zicheng Xu, Guanchu Wang, Yu-Neng Chuang, Guangyao Zheng, Alexander S. Szalay, Zirui Liu, Vladimir Braverman

CoRR, November, 2025

Training-Free Time Series Classification via In-Context Reasoning with LLM Agents.

Songyuan Sui, Zihang Xu, Yu-Neng Chuang, Kwei-Herng Lai, Xia Hu

CoRR, October, 2025

AutoL2S: Auto Long-Short Reasoning for Efficient Large Language Models.

Feng Luo, Yu-Neng Chuang, Guanchu Wang, Hoang Anh Duy Le, Shaochen Zhong, Hongyi Liu, Jiayi Yuan, Yang Sui, Vladimir Braverman, Vipin Chaudhary, Xia Hu

CoRR, May, 2025

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

Yang Sui, Yu-Neng Chuang, Guanchu Wang, Jiamu Zhang, Tianyi Zhang, Jiayi Yuan, Hongyi Liu, Andrew Wen, Shaochen Zhong, Hanjie Chen, Xia Ben Hu

CoRR, March, 2025

Fair-RGNN: Mitigating Relational Bias on Knowledge Graphs.

Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang, Mengnan Du, Chia-Yuan Chang, Na Zou, Xia Hu

ACM Trans. Knowl. Discov. Data, February, 2025

Confident or Seek Stronger: Exploring Uncertainty-Based On-device LLM Routing From Benchmarking to Generalization.

Yu-Neng Chuang, Leisheng Yu, Guanchu Wang, Lizhe Zhang, Zirui Liu, Xuanting Cai, Yang Sui, Vladimir Braverman, Xia Ben Hu

CoRR, February, 2025

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

Yang Sui, Yu-Neng Chuang, Guanchu Wang, Jiamu Zhang, Tianyi Zhang, Jiayi Yuan, Hongyi Liu, Andrew Wen, Shaochen Zhong, Na Zou, Hanjie Chen, Xia Hu

Trans. Mach. Learn. Res., 2025

DHP Benchmark: Are LLMs Good NLG Evaluators?

Yicheng Wang, Jiayi Yuan, Yu-Neng Chuang, Zhuoer Wang, Yingchi Liu, Mark Cusick, Param Kulkarni, Zhengping Ji, Yasser Ibrahim, Xia Hu

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2025, Albuquerque, New Mexico, USA, April 29, 2025

CODA: Temporal Domain Generalization via Concept Drift Simulator.

Chia-Yuan Chang, Yu-Neng Chuang, Zhimeng Jiang, Kwei-Herng Lai, Anxiao Jiang, Na Zou

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Learning to Route LLMs with Confidence Tokens.

Yu-Neng Chuang, Prathusha Kameswara Sarma, Parikshit Gopalan, John Boccio, Sara Bolouki, Xia Hu, Helen Zhou

Proceedings of the Forty-second International Conference on Machine Learning, 2025

A Decoupled Multi-Agent Framework for Complex Text Style Transfer.

Lingxi Zhang, Yu-Neng Chuang, Guanchu Wang, Ruixiang Tang, Xuanting Cai, Rajesh Shenoy, Xia Hu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Self-Ensemble: Mitigating Confidence Distortion for Large Language Models.

Zicheng Xu, Guanchu Wang, Guangyao Zheng, Yu-Neng Chuang, Alex Szalay, Xia Hu, Vladimir Braverman

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

LoRATK: LoRA Once, Backdoor Everywhere in the Share-and-Play Ecosystem.

Hongyi Liu, Shaochen Zhong, Xintong Sun, Minghao Tian, Mohsen Hariri, Zirui Liu, Ruixiang Tang, Zhimeng Jiang, Jiayi Yuan, Yu-Neng Chuang, Li Li, Soo-Hyun Choi, Rui Chen, Vipin Chaudhary, Xia Hu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Quantized Can Still Be Calibrated: A Unified Framework to Calibration in Quantized Large Language Models.

Mingyu Zhong, Guanchu Wang, Yu-Neng Chuang, Na Zou

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

ReasonerRank: Redefining Language Model Evaluation with Ground-Truth-Free Ranking Frameworks.

Jiamu Zhang, Jiayi Yuan, Andrew Wen, Hoang Anh Duy Le, Yu-Neng Chuang, Soo-Hyun Choi, Rui Chen, Xia Hu

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

The Science of Detecting LLM-Generated Text.

Ruixiang Tang, Yu-Neng Chuang, Xia Hu

Commun. ACM, April, 2024

SPeC: A Soft Prompt-Based Calibration on Performance Variability of Large Language Model in Clinical Notes Summarization.

Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu

J. Biomed. Informatics, 2024

Learning to Route with Confidence Tokens.

Yu-Neng Chuang, Helen Zhou, Prathusha Kameswara Sarma, Parikshit Gopalan, John Boccio, Sara Bolouki, Xia Hu

CoRR, 2024

Assessing and Enhancing Large Language Models in Rare Disease Question-answering.

Guanchu Wang, Junhao Ran, Ruixiang Tang, Chia-Yuan Chang, Yu-Neng Chuang, Zirui Liu, Vladimir Braverman, Zhandong Liu, Xia Hu

CoRR, 2024

Understanding Different Design Choices in Training Large Time Series Models.

Yu-Neng Chuang, Songchen Li, Jiayi Yuan, Guanchu Wang, Kwei-Herng Lai, Leisheng Yu, Sirui Ding, Chia-Yuan Chang, Qiaoyu Tan, Daochen Zha, Xia Hu

CoRR, 2024

GraphFM: A Comprehensive Benchmark for Graph Foundation Model.

Yuhao Xu, Xinqi Liu, Keyu Duan, Yi Fang, Yu-Neng Chuang, Daochen Zha, Qiaoyu Tan

CoRR, 2024

Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data.

Aokun Chen, Qian Li, Yu Huang, Yongqiu Li, Yu-Neng Chuang, Xia Hu, Serena Guo, Yonghui Wu, Yi Guo, Jiang Bian

CoRR, 2024

Large Language Models As Faithful Explainers.

Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Ruixiang Tang, Fan Yang, Mengnan Du, Xuanting Cai, Xia Hu

CoRR, 2024

Secure Your Model: An Effective Key Prompt Protection Mechanism for Large Language Models.

Ruixiang Tang, Yu-Neng Chuang, Xuanting Cai, Mengnan Du, Xia Hu

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

Learning to Compress Prompt in Natural Language Formats.

Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang, Zirui Liu, Xun Chen, Xia Ben Hu

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

TVE: Learning Meta-attribution for Transferable Vision Explainer.

Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu

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

KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches.

Jiayi Yuan, Hongyi Liu, Shaochen (Henry) Zhong, Yu-Neng Chuang, Songchen Li, Guanchu Wang, Duy Le, Hongye Jin, Vipin Chaudhary, Zhaozhuo Xu, Zirui Liu, Xia Ben Hu

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

Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion.

Guanchu Wang, Yu-Neng Chuang, Ruixiang Tang, Shaochen Zhong, Jiayi Yuan, Hongye Jin, Zirui Liu, Vipin Chaudhary, Shuai Xu, James Caverlee, Xia Ben Hu

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

2023

LETA: Learning Transferable Attribution for Generic Vision Explainer.

Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu

CoRR, 2023

DISPEL: Domain Generalization via Domain-Specific Liberating.

Chia-Yuan Chang, Yu-Neng Chuang, Guanchu Wang, Mengnan Du, Zou Na

CoRR, 2023

Towards Assumption-free Bias Mitigation.

Chia-Yuan Chang, Yu-Neng Chuang, Kwei-Herng Lai, Xiaotian Han, Xia Hu, Na Zou

CoRR, 2023

SPeC: A Soft Prompt-Based Calibration on Mitigating Performance Variability in Clinical Notes Summarization.

Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu

CoRR, 2023

The Science of Detecting LLM-Generated Texts.

Ruixiang Tang, Yu-Neng Chuang, Xia Hu

CoRR, 2023

Efficient XAI Techniques: A Taxonomic Survey.

Yu-Neng Chuang, Guanchu Wang, Fan Yang, Zirui Liu, Xuanting Cai, Mengnan Du, Xia Ben Hu

CoRR, 2023

CoRTX: Contrastive Framework for Real-time Explanation.

Yu-Neng Chuang, Guanchu Wang, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research.

Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Kwei-Herng Lai, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla-Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Hu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Mitigating Relational Bias on Knowledge Graphs.

Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang, Mengnan Du, Chia-Yuan Chang, Na Zou, Xia Hu

CoRR, 2022

Accelerating Shapley Explanation via Contributive Cooperator Selection.

Guanchu Wang, Yu-Neng Chuang, Mengnan Du, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu

Proceedings of the International Conference on Machine Learning, 2022

2020

Skewness Ranking Optimization for Personalized Recommendation.

Yu-Neng Chuang, Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

TPR: Text-aware Preference Ranking for Recommender Systems.

Yu-Neng Chuang, Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai, Yuan Fang, Ee-Peng Lim

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Negative-Aware Collaborative Filtering.

Sheng-Chieh Lin, Yu-Neng Chuang, Sheng-Fang Yang, Ming-Feng Tsai, Chuan-Ju Wang

Proceedings of ACM RecSys 2019 Late-Breaking Results co-located with the 13th ACM Conference on Recommender Systems, 2019

2017

Variational grid setting network.

Yu-Neng Chuang, Zi-Yu Huang, Yen-Lung Tsai

Proceedings of the 2017 International Conference on Asian Language Processing, 2017