Automatic Bridge Bidding Using Deep Reinforcement Learning. - Chih-Kuan Yeh; Hsuan-Tien Lin (ECAI, 2016)

An Improved Tax Scheme for Selfish Routing. - Te-Li Wang; Chih-Kuan Yeh; Ho-Lin Chen (ISAAC, 2016)

Learning graph fusion for query and database specific image retrieval. - Chih-Kuan Yeh; Wei-Chieh Wu; Yu-Chiang Frank Wang (MMSP, 2016)

Learning Deep Latent Space for Multi-Label Classification. - Chih-Kuan Yeh; Wei-Chieh Wu; Wei-Jen Ko; Yu-Chiang Frank Wang (AAAI, 2017)

Generative-Discriminative Variational Model for Visual Recognition. - Chih-Kuan Yeh; Yao-Hung Hubert Tsai; Yu-Chiang Frank Wang (CoRR, 2017)

Learning Deep Latent Spaces for Multi-Label Classification. - Chih-Kuan Yeh; Wei-Chieh Wu; Wei-Jen Ko; Yu-Chiang Frank Wang (CoRR, 2017)

Order-Free RNN With Visual Attention for Multi-Label Classification. - Shang-Fu Chen; Yi-Chen Chen; Chih-Kuan Yeh; Yu-Chiang Frank Wang (AAAI, 2018)

Multi-Label Zero-Shot Learning With Structured Knowledge Graphs. - Chung-Wei Lee; Wei Fang; Chih-Kuan Yeh; Yu-Chiang Frank Wang (CVPR, 2018)

Deep Generative Models for Weakly-Supervised Multi-Label Classification. - Hong-Min Chu; Chih-Kuan Yeh; Yu-Chiang Frank Wang (ECCV (2), 2018)

Representer Point Selection for Explaining Deep Neural Networks. - Chih-Kuan Yeh; Joon Sik Kim; Ian En-Hsu Yen; Pradeep Ravikumar (NeurIPS, 2018)

Automatic Bridge Bidding Using Deep Reinforcement Learning. - Chih-Kuan Yeh; Cheng-Yu Hsieh; Hsuan-Tien Lin (IEEE Trans. Games, 2018)

Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching. - Chih-Kuan Yeh; Jianshu Chen; Chengzhu Yu; Dong Yu 001 (ICLR (Poster), 2019)

On the (In)fidelity and Sensitivity of Explanations. - Chih-Kuan Yeh; Cheng-Yu Hsieh; Arun Sai Suggala; David I. Inouye; Pradeep Ravikumar (NeurIPS, 2019)

How Sensitive are Sensitivity-Based Explanations? - Chih-Kuan Yeh; Cheng-Yu Hsieh; Arun Sai Suggala; David I. Inouye; Pradeep Ravikumar (CoRR, 2019)

On Concept-Based Explanations in Deep Neural Networks. - Chih-Kuan Yeh; Been Kim; Sercan Ömer Arik; Chun-Liang Li; Pradeep Ravikumar; Tomas Pfister (CoRR, 2019)

Minimizing FLOPs to Learn Efficient Sparse Representations. - Biswajit Paria; Chih-Kuan Yeh; Ian En-Hsu Yen; Ning Xu; Pradeep Ravikumar; Barnabás Póczos (ICLR, 2020)

On Completeness-aware Concept-Based Explanations in Deep Neural Networks. - Chih-Kuan Yeh; Been Kim; Sercan Ömer Arik; Chun-Liang Li; Tomas Pfister; Pradeep Ravikumar (NeurIPS, 2020)

Evaluations and Methods for Explanation through Robustness Analysis. - Cheng-Yu Hsieh; Chih-Kuan Yeh; Xuanqing Liu; Pradeep Kumar Ravikumar; Seungyeon Kim 001; Sanjiv Kumar; Cho-Jui Hsieh (ICLR, 2021)

Human-Centered Concept Explanations for Neural Networks. - Chih-Kuan Yeh; Been Kim; Pradeep Ravikumar (Neuro-Symbolic Artificial Intelligence, 2021)

Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations. - Chih-Kuan Yeh; Kuan-Yun Lee; Frederick Liu; Pradeep Ravikumar (AISTATS, 2022)

First is Better Than Last for Language Data Influence. - Chih-Kuan Yeh; Ankur Taly; Mukund Sundararajan; Frederick Liu; Pradeep Ravikumar (NeurIPS, 2022)

First is Better Than Last for Training Data Influence. - Chih-Kuan Yeh; Ankur Taly; Mukund Sundararajan; Frederick Liu; Pradeep Ravikumar (CoRR, 2022)

Human-Centered Concept Explanations for Neural Networks. - Chih-Kuan Yeh; Been Kim; Pradeep Ravikumar (CoRR, 2022)

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 (ACL (Findings), 2023)

Concept Gradient: Concept-based Interpretation Without Linear Assumption. - Andrew Bai; Chih-Kuan Yeh; Neil Y. C. Lin; Pradeep Kumar Ravikumar; Cho-Jui Hsieh (ICLR, 2023)

Order Matters in the Presence of Dataset Imbalance for Multilingual Learning. - Dami Choi; Derrick Xin; Hamid Dadkhahi; Justin Gilmer; Ankush Garg; Orhan Firat; Chih-Kuan Yeh; Andrew M. Dai; Behrooz Ghorbani (NeurIPS, 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)

Which Pretrain Samples to Rehearse when Finetuning Pretrained Models? - Andrew Bai; Chih-Kuan Yeh; Cho-Jui Hsieh; Ankur Taly (CoRR, 2024)

Scalable Multi-Domain Adaptation of Language Models using Modular Experts. - Peter Schafhalter; Shun Liao; Yanqi Zhou; Chih-Kuan Yeh; Arun Kandoor; James Laudon (CoRR, 2024)

An Efficient Rehearsal Scheme for Catastrophic Forgetting Mitigation during Multi-stage Fine-tuning. - Andrew Bai; Chih-Kuan Yeh; Cho-Jui Hsieh; Ankur Taly (NAACL (Findings), 2025)