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Jiefeng Chen

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Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs

Oct 18, 2023
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan O Arik, Tomas Pfister, Somesh Jha

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Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection

May 27, 2023
Nils Palumbo, Yang Guo, Xi Wu, Jiefeng Chen, Yingyu Liang, Somesh Jha

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Stratified Adversarial Robustness with Rejection

May 12, 2023
Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha

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ASPEST: Bridging the Gap Between Active Learning and Selective Prediction

Apr 07, 2023
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Arik, Somesh Jha, Tomas Pfister

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Is forgetting less a good inductive bias for forward transfer?

Mar 14, 2023
Jiefeng Chen, Timothy Nguyen, Dilan Gorur, Arslan Chaudhry

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The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning

Feb 28, 2023
Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha

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Concept-based Explanations for Out-Of-Distribution Detectors

Mar 04, 2022
Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash

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Towards Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-based Method

Nov 19, 2021
Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li, Alex Kot

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Towards Evaluating the Robustness of Neural Networks Learned by Transduction

Oct 27, 2021
Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha

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