Chih-Kuan Yeh

According to our database, Chih-Kuan Yeh authored at least 30 papers between 2016 and 2024.

Collaborative distances:

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

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

Which Pretrain Samples to Rehearse when Finetuning Pretrained Models?

Andrew Bai, Chih-Kuan Yeh, Cho-Jui Hsieh, Ankur Taly

CoRR, 2024

2023

Faith-Shap: The Faithful Shapley Interaction Index.

Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar

J. Mach. Learn. Res., 2023

Sample based Explanations via Generalized Representers.

Che-Ping Tsai, Chih-Kuan Yeh, Pradeep Ravikumar

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

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

Concept Gradient: Concept-based Interpretation Without Linear Assumption.

Andrew Bai, Chih-Kuan Yeh, Neil Y. C. Lin, Pradeep Kumar Ravikumar, Cho-Jui Hsieh

Proceedings of the Eleventh International Conference on Learning Representations, 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

Human-Centered Concept Explanations for Neural Networks.

Chih-Kuan Yeh, Been Kim, Pradeep Ravikumar

CoRR, 2022

First is Better Than Last for Training Data Influence.

Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar

CoRR, 2022

First is Better Than Last for Language Data Influence.

Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar

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

Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations.

Chih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu, Pradeep Ravikumar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Human-Centered Concept Explanations for Neural Networks.

Chih-Kuan Yeh, Been Kim, Pradeep Ravikumar

Proceedings of the Neuro-Symbolic Artificial Intelligence: The State of the Art, 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

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Minimizing FLOPs to Learn Efficient Sparse Representations.

Biswajit Paria, Chih-Kuan Yeh, Ian En-Hsu Yen, Ning Xu, Pradeep Ravikumar, Barnabás Póczos

Proceedings of the 8th International Conference on Learning Representations, 2020

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

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

Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching.

Chih-Kuan Yeh, Jianshu Chen, Chengzhu Yu, Dong Yu

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Automatic Bridge Bidding Using Deep Reinforcement Learning.

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

IEEE Trans. Games, 2018

Representer Point Selection for Explaining Deep Neural Networks.

Chih-Kuan Yeh, Joon Sik Kim, Ian En-Hsu Yen, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Generative Models for Weakly-Supervised Multi-Label Classification.

Hong-Min Chu, Chih-Kuan Yeh, Yu-Chiang Frank Wang

Proceedings of the Computer Vision - ECCV 2018, 2018

Multi-Label Zero-Shot Learning With Structured Knowledge Graphs.

Chung-Wei Lee, Wei Fang, Chih-Kuan Yeh, Yu-Chiang Frank Wang

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Order-Free RNN With Visual Attention for Multi-Label Classification.

Shang-Fu Chen, Yi-Chen Chen, Chih-Kuan Yeh, Yu-Chiang Frank Wang

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

2017

Learning Deep Latent Spaces for Multi-Label Classification.

Chih-Kuan Yeh, Wei-Chieh Wu, Wei-Jen Ko, Yu-Chiang Frank Wang

CoRR, 2017

Generative-Discriminative Variational Model for Visual Recognition.

Chih-Kuan Yeh, Yao-Hung Hubert Tsai, Yu-Chiang Frank Wang

CoRR, 2017

Learning Deep Latent Space for Multi-Label Classification.

Chih-Kuan Yeh, Wei-Chieh Wu, Wei-Jen Ko, Yu-Chiang Frank Wang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Learning graph fusion for query and database specific image retrieval.

Chih-Kuan Yeh, Wei-Chieh Wu, Yu-Chiang Frank Wang

Proceedings of the 18th IEEE International Workshop on Multimedia Signal Processing, 2016

An Improved Tax Scheme for Selfish Routing.

Te-Li Wang, Chih-Kuan Yeh, Ho-Lin Chen

Proceedings of the 27th International Symposium on Algorithms and Computation, 2016

Automatic Bridge Bidding Using Deep Reinforcement Learning.

Chih-Kuan Yeh, Hsuan-Tien Lin

Proceedings of the ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands, 2016