Jiefeng Chen - RankMe

47 papers A* 10A 2B 1Journal 31Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MARS: Modular Agent with Reflective Search for Automated AI Research. CoRR Jiefeng Chen, Bhavana Dalvi Mishra, Jaehyun Nam, Rui Meng, Tomas Pfister, Jinsung Yoon
2025	J	`jnl`	ATLAS: Constraints-Aware Multi-Agent Collaboration for Real-World Travel Planning. CoRR Jihye Choi, Jinsung Yoon, Jiefeng Chen, Somesh Jha, Tomas Pfister
2025	—	`conf`	Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models. ACL (1) Fei Wang, Xingchen Wan, Ruoxi Sun, Jiefeng Chen, Sercan Ö. Arik
2025	J	`jnl`	CoDA: Agentic Systems for Collaborative Data Visualization. CoRR Zichen Chen, Jiefeng Chen, Sercan Ö. Arik, Misha Sra, Tomas Pfister, Jinsung Yoon
2025	J	`jnl`	DS-STAR: Data Science Agent via Iterative Planning and Verification. CoRR Jaehyun Nam, Jinsung Yoon, Jiefeng Chen, Tomas Pfister
2025	J	`jnl`	DynScaling: Efficient Verifier-free Inference Scaling via Dynamic and Integrated Sampling. CoRR Fei Wang, Xingchen Wan, Ruoxi Sun, Jiefeng Chen, Sercan Ö. Arik
2025	J	`jnl`	MLE-STAR: Machine Learning Engineering Agent via Search and Targeted Refinement. CoRR Jaehyun Nam, Jinsung Yoon, Jiefeng Chen, Jinwoo Shin, Sercan Ö. Arik, Tomas Pfister
2025	J	`jnl`	SETS: Leveraging Self-Verification and Self-Correction for Improved Test-Time Scaling. CoRR Jiefeng Chen, Jie Ren, Xinyun Chen, Chengrun Yang, Ruoxi Sun, Sercan Ö. Arik
2025	J	`jnl`	SETS: Leveraging Self-Verification and Self-Correction for Improved Test-Time Scaling. Trans. Mach. Learn. Res. Jiefeng Chen, Jie Ren, Xinyun Chen, Chengrun Yang, Ruoxi Sun, Jinsung Yoon, Sercan Ö. Arik
2024	J	`jnl`	ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. Trans. Mach. Learn. Res. Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister
2024	J	`jnl`	Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models. CoRR Fei Wang, Xingchen Wan, Ruoxi Sun, Jiefeng Chen, Sercan Ö. Arik
2024	A*	`conf`	Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection. ICML Nils Palumbo, Yang Guo, Xi Wu, Jiefeng Chen, Yingyu Liang, Somesh Jha
2023	J	`jnl`	ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. CoRR Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister
2023	—	`conf`	Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. EMNLP (Findings) Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha
2023	J	`jnl`	Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. CoRR Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha
2023	A*	`conf`	Concept-based Explanations for Out-of-Distribution Detectors. ICML Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash
2023	A*	`conf`	Is Forgetting Less a Good Inductive Bias for Forward Transfer? ICLR Jiefeng Chen, Timothy Nguyen, Dilan Görür, Arslan Chaudhry
2023	J	`jnl`	Is forgetting less a good inductive bias for forward transfer? CoRR Jiefeng Chen, Timothy Nguyen, Dilan Görür, Arslan Chaudhry
2023	A*	`conf`	Stratified Adversarial Robustness with Rejection. ICML Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha
2023	J	`jnl`	Stratified Adversarial Robustness with Rejection. CoRR Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha
2023	A*	`conf`	The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. ICLR Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha
2023	J	`jnl`	The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. CoRR Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha
2023	J	`jnl`	Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection. CoRR Nils Palumbo, Yang Guo, Xi Wu, Jiefeng Chen, Yingyu Liang, Somesh Jha
2022	J	`jnl`	Concept-based Explanations for Out-Of-Distribution Detectors. CoRR Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash
2022	A	`conf`	GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems. EuroS&P Ryan Feng, Neal Mangaokar, Jiefeng Chen, Earlence Fernandes, Somesh Jha, Atul Prakash
2022	J	`jnl`	Toward Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-Based Method. IEEE Internet Things J. Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li, Alex ChiChung Kot
2022	A*	`conf`	Towards Evaluating the Robustness of Neural Networks Learned by Transduction. ICLR Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha
2021	B	`conf`	AI-GAN: Attack-Inspired Generation of Adversarial Examples. ICIP Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li, Alex C. Kot
2021	—	`conf`	ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining. ECML/PKDD (3) Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha
2021	A*	`conf`	Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. NeurIPS Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha
2021	J	`jnl`	Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. CoRR Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha
2021	J	`jnl`	Towards Adversarial Robustness via Transductive Learning. CoRR Jiefeng Chen, Yang Guo, Xi Wu, Tianqi Li, Qicheng Lao, Yingyu Liang, Somesh Jha
2021	J	`jnl`	Towards Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-based Method. CoRR Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li, Alex C. Kot
2021	J	`jnl`	Towards Evaluating the Robustness of Neural Networks Learned by Transduction. CoRR Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha
2020	J	`jnl`	AI-GAN: Attack-Inspired Generation of Adversarial Examples. CoRR Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li
2020	A*	`conf`	Concise Explanations of Neural Networks using Adversarial Training. ICML Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Xi Wu, Somesh Jha
2020	J	`jnl`	Query-Efficient Physical Hard-Label Attacks on Deep Learning Visual Classification. CoRR Ryan Feng, Jiefeng Chen, Nelson R. Manohar, Earlence Fernandes, Somesh Jha, Atul Prakash
2020	J	`jnl`	Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation. CoRR Xi Wu, Yang Guo, Jiefeng Chen, Yingyu Liang, Somesh Jha, Prasad Chalasani
2020	J	`jnl`	Robust Out-of-distribution Detection in Neural Networks. CoRR Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha
2020	J	`jnl`	Robust Out-of-distribution Detection via Informative Outlier Mining. CoRR Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha
2019	A*	`conf`	Robust Attribution Regularization. NeurIPS Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha
2019	J	`jnl`	Robust Attribution Regularization. CoRR Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha
2019	A	`conf`	Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks. EuroS&P Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha
2018	J	`jnl`	Concise Explanations of Neural Networks using Adversarial Training. CoRR Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Somesh Jha, Xi Wu
2018	J	`jnl`	Improving Adversarial Robustness by Data-Specific Discretization. CoRR Jiefeng Chen, Xi Wu, Yingyu Liang, Somesh Jha
2018	A*	`conf`	Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training. ICML Xi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh Jha
2017	J	`jnl`	ReabsNet: Detecting and Revising Adversarial Examples. CoRR Jiefeng Chen, Zihang Meng, Changtian Sun, Wei Tang, Yinglun Zhu