Transcribing Lyrics from Commercial Song Audio: the First Step Towards Singing Content Processing. - Che-Ping Tsai; Yi-Lin Tuan; Lin-Shan Lee (ICASSP, 2018)

Adversarial Learning of Label Dependency: A Novel Framework for Multi-class Classification. - Che-Ping Tsai; Hung-yi Lee (ICASSP, 2019)

Completely Unsupervised Phoneme Recognition by a Generative Adversarial Network Harmonized with Iteratively Refined Hidden Markov Models. - Kuan-Yu Chen 005; Che-Ping Tsai; Da-Rong Liu; Hung-yi Lee; Lin-Shan Lee (INTERSPEECH, 2019)

Order-Free Learning Alleviating Exposure Bias in Multi-Label Classification. - Che-Ping Tsai; Hung-yi Lee (AAAI, 2020)

Heavy-tailed Streaming Statistical Estimation. - Che-Ping Tsai; Adarsh Prasad; Sivaraman Balakrishnan; Pradeep Ravikumar (AISTATS, 2022)

Representer Point Selection for Explaining Regularized High-dimensional Models. - Che-Ping Tsai; Jiong Zhang; Hsiang-Fu Yu; Eli Chien; Cho-Jui Hsieh; Pradeep Kumar Ravikumar (ICML, 2023)

Sample based Explanations via Generalized Representers. - Che-Ping Tsai; Chih-Kuan Yeh; Pradeep Ravikumar (NeurIPS, 2023)

Faith-Shap: The Faithful Shapley Interaction Index. - Che-Ping Tsai; Chih-Kuan Yeh; Pradeep Ravikumar (J. Mach. Learn. Res., 2023)

An Effective ECO Methodology for Reducing Back-side Design Rule Violations in Double-sided Signal Routing. - Che-Ping Tsai; Fang-Yu Hsu; Wai-Kei Mak; Ting-Chi Wang (ICCAD, 2024)

CLUE: Concept-Level Uncertainty Estimation for Large Language Models. - Yu-Hsiang Wang; Andrew Bai; Che-Ping Tsai; Cho-Jui Hsieh (CoRR, 2024)

AnoLLM: Large Language Models for Tabular Anomaly Detection. - Che-Ping Tsai; Ganyu Teng; Phillip Wallis; Wei Ding (ICLR, 2025)

Contextures: Representations from Contexts. - Runtian Zhai; Kai Yang; Che-Ping Tsai; Burak Varici; Zico Kolter; Pradeep Ravikumar (CoRR, 2025)