Tsui-Wei Weng - RankMe

106 papers A* 30A 2Journal 68Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning. Trans. Mach. Learn. Res. Amirhosein Javadi, Tuomas P. Oikarinen, Tara Javidi, Tsui-Wei Weng
2026	J	`jnl`	Distance Marching for Generative Modeling. CoRR Zimo Wang, Ishit Mehta, Haolin Lu, Chung-En Sun, Ge Yan, Tsui-Wei Weng, Tzu-Mao Li
2026	J	`jnl`	Graph Concept Bottleneck Models. Trans. Mach. Learn. Res. Haotian Xu, Tsui-Wei Weng, Lam M. Nguyen, Tengfei Ma
2026	J	`jnl`	Steer2Edit: From Activation Steering to Component-Level Editing. CoRR Chung-En Sun, Ge Yan, Zimo Wang, Tsui-Wei Weng
2025	A*	`conf`	Anti-Sensing: Defense Against Unauthorized Radar-Based Human Vital Sign Sensing with Physically Realizable Wearable Oscillators. ICRA Md. Farhan Tasnim Oshim, Nigel Doering, Bashima Islam, Tsui-Wei Weng, Tauhidur Rahman
2025	J	`jnl`	Anti-Sensing: Defense against Unauthorized Radar-based Human Vital Sign Sensing with Physically Realizable Wearable Oscillators. CoRR Md. Farhan Tasnim Oshim, Nigel Doering, Bashima Islam, Tsui-Wei Weng, Tauhidur Rahman
2025	A*	`conf`	Concept Bottleneck Large Language Models. ICLR Chung-En Sun, Tuomas P. Oikarinen, Berk Ustun, Tsui-Wei Weng
2025	—	`conf`	Effective Skill Unlearning through Intervention and Abstention. NAACL (Long Papers) Yongce Li, Chung-En Sun, Tsui-Wei Weng
2025	J	`jnl`	Effective Skill Unlearning through Intervention and Abstention. CoRR Yongce Li, Chung-En Sun, Tsui-Wei Weng
2025	A*	`conf`	Evaluating Neuron Explanations: A Unified Framework with Sanity Checks. ICML Tuomas P. Oikarinen, Ge Yan, Tsui-Wei Weng
2025	J	`jnl`	Evaluating Neuron Explanations: A Unified Framework with Sanity Checks. CoRR Tuomas P. Oikarinen, Ge Yan, Tsui-Wei Weng
2025	J	`jnl`	Faithful and Stable Neuron Explanations for Trustworthy Mechanistic Interpretability. CoRR Ge Yan, Tuomas P. Oikarinen, Tsui-Wei Weng
2025	J	`jnl`	Graph Concept Bottleneck Models. CoRR Haotian Xu, Tsui-Wei Weng, Lam M. Nguyen, Tengfei Ma
2025	A*	`conf`	Interpretable Generative Models through Post-hoc Concept Bottlenecks. CVPR Akshay R. Kulkarni, Ge Yan, Chung-En Sun, Tuomas P. Oikarinen, Tsui-Wei Weng
2025	J	`jnl`	Interpretable Generative Models through Post-hoc Concept Bottlenecks. CoRR Akshay R. Kulkarni, Ge Yan, Chung-En Sun, Tuomas P. Oikarinen, Tsui-Wei Weng
2025	J	`jnl`	Interpretable and Steerable Concept Bottleneck Sparse Autoencoders. CoRR Akshay Kulkarni, Tsui-Wei Weng, Vivek Sivaraman Narayanaswamy, Shusen Liu, Wesam A. Sakla, Kowshik Thopalli
2025	J	`jnl`	Interpreting Neurons in Deep Vision Networks with Language Models. Trans. Mach. Learn. Res. Nicholas Bai, Rahul A. Iyer, Tuomas P. Oikarinen, Akshay R. Kulkarni, Tsui-Wei Weng
2025	—	`conf`	Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities. NAACL (Long Papers) Chung-En Sun, Xiaodong Liu, Weiwei Yang, Tsui-Wei Weng, Hao Cheng, Aidan San, Michel Galley, Jianfeng Gao
2025	J	`jnl`	Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data. CoRR Pei-Yau Weng, Minh Hoang, Lam M. Nguyen, My T. Thai, Tsui-Wei Weng, Trong Nghia Hoang
2025	J	`jnl`	RAT: Boosting Misclassification Detection Ability without Extra Data. CoRR Ge Yan, Tsui-Wei Weng
2025	J	`jnl`	ReFIne: A Framework for Trustworthy Large Reasoning Models with Reliability, Faithfulness, and Interpretability. CoRR Chung-En Sun, Ge Yan, Akshay R. Kulkarni, Tsui-Wei Weng
2025	J	`jnl`	ReflCtrl: Controlling LLM Reflection via Representation Engineering. CoRR Ge Yan, Chung-En Sun, Tsui-Wei Weng
2025	J	`jnl`	Resting Neurons, Active Insights: Improving Input Sparsification for Large Language Models. CoRR Haotian Xu, Tian Gao, Tsui-Wei Weng, Tengfei Ma
2025	J	`jnl`	Rethinking Crowd-Sourced Evaluation of Neuron Explanations. CoRR Tuomas P. Oikarinen, Ge Yan, Akshay R. Kulkarni, Tsui-Wei Weng
2025	A	`conf`	SAND: Enhancing Open-Set Neuron Descriptions through Spatial Awareness. WACV Anvita A. Srinivas, Tuomas P. Oikarinen, Divyansh Srivastava, Wei-Hung Weng, Tsui-Wei Weng
2025	J	`jnl`	Statistical Inference for Responsiveness Verification. CoRR Seung Hyun Cheon, Meredith Stewart, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
2025	A*	`conf`	ThinkEdit: Interpretable Weight Editing to Mitigate Overly Short Thinking in Reasoning Models. EMNLP Chung-En Sun, Ge Yan, Tsui-Wei Weng
2025	J	`jnl`	ThinkEdit: Interpretable Weight Editing to Mitigate Overly Short Thinking in Reasoning Models. CoRR Chung-En Sun, Ge Yan, Tsui-Wei Weng
2025	A*	`conf`	Understanding Fixed Predictions via Confined Regions. ICML Connor Lawless, Tsui-Wei Weng, Berk Ustun, Madeleine Udell
2025	J	`jnl`	Understanding Fixed Predictions via Confined Regions. CoRR Connor Lawless, Tsui-Wei Weng, Berk Ustun, Madeleine Udell
2024	A*	`conf`	AND: Audio Network Dissection for Interpreting Deep Acoustic Models. ICML Tung-Yu Wu, Yu-Xiang Lin, Tsui-Wei Weng
2024	J	`jnl`	AND: Audio Network Dissection for Interpreting Deep Acoustic Models. CoRR Tung-Yu Wu, Yu-Xiang Lin, Tsui-Wei Weng
2024	J	`jnl`	Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-series Classification. CoRR Yunshi Wen, Tengfei Ma, Tsui-Wei Weng, Lam M. Nguyen, Anak Agung Julius
2024	A*	`conf`	Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents. ICML Chung-En Sun, Sicun Gao, Tsui-Wei Weng
2024	J	`jnl`	Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents. CoRR Chung-En Sun, Sicun Gao, Tsui-Wei Weng
2024	J	`jnl`	Concept Bottleneck Large Language Models. CoRR Chung-En Sun, Tuomas P. Oikarinen, Berk Ustun, Tsui-Wei Weng
2024	J	`jnl`	Concept-Driven Continual Learning. Trans. Mach. Learn. Res. Sin-Han Yang, Tuomas P. Oikarinen, Tsui-Wei Weng
2024	J	`jnl`	Crafting Large Language Models for Enhanced Interpretability. CoRR Chung-En Sun, Tuomas P. Oikarinen, Tsui-Wei Weng
2024	J	`jnl`	Describe-and-Dissect: Interpreting Neurons in Vision Networks with Language Models. CoRR Nicholas Bai, Rahul A. Iyer, Tuomas P. Oikarinen, Tsui-Wei Weng
2024	—	`conf`	Interpretability-Guided Test-Time Adversarial Defense. ECCV (37) Akshay R. Kulkarni, Tsui-Wei Weng
2024	J	`jnl`	Interpretability-Guided Test-Time Adversarial Defense. CoRR Akshay R. Kulkarni, Tsui-Wei Weng
2024	J	`jnl`	Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities. CoRR Chung-En Sun, Xiaodong Liu, Weiwei Yang, Tsui-Wei Weng, Hao Cheng, Aidan San, Michel Galley, Jianfeng Gao
2024	A*	`conf`	Linear Explanations for Individual Neurons. ICML Tuomas P. Oikarinen, Tsui-Wei Weng
2024	J	`jnl`	Linear Explanations for Individual Neurons. CoRR Tuomas P. Oikarinen, Tsui-Wei Weng
2024	A*	`conf`	Prediction without Preclusion: Recourse Verification with Reachable Sets. ICLR Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
2024	A*	`conf`	Provably Robust Conformal Prediction with Improved Efficiency. ICLR Ge Yan, Yaniv Romano, Tsui-Wei Weng
2024	J	`jnl`	Provably Robust Conformal Prediction with Improved Efficiency. CoRR Ge Yan, Yaniv Romano, Tsui-Wei Weng
2024	J	`jnl`	VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance. CoRR Divyansh Srivastava, Ge Yan, Tsui-Wei Weng
2023	J	`jnl`	Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection. Trans. Mach. Learn. Res. Wei Huang, Chunrui Liu, Yilan Chen, Richard Yi Da Xu, Miao Zhang, Tsui-Wei Weng
2023	A*	`conf`	Attacking c-MARL More Effectively: A Data Driven Approach. ICDM Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng
2023	A*	`conf`	CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks. ICLR Tuomas P. Oikarinen, Tsui-Wei Weng
2023	J	`jnl`	Certified Interpretability Robustness for Class Activation Mapping. CoRR Alex Gu, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2023	A*	`conf`	ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. ICML Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen
2023	J	`jnl`	ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction. CoRR Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen
2023	J	`jnl`	Concept-Monitor: Understanding DNN training through individual neurons. CoRR Mohammad Ali Khan, Tuomas P. Oikarinen, Tsui-Wei Weng
2023	J	`jnl`	Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies. CoRR Ligong Han, Seungwook Han, Shivchander Sudalairaj, Charlotte Loh, Rumen Dangovski, Fei Deng, Pulkit Agrawal, Dimitris N. Metaxas, Leonid Karlinsky, Tsui-Wei Weng, Akash Srivastava
2023	A*	`conf`	Corrupting Neuron Explanations of Deep Visual Features. ICCV Divyansh Srivastava, Tuomas P. Oikarinen, Tsui-Wei Weng
2023	J	`jnl`	Corrupting Neuron Explanations of Deep Visual Features. CoRR Divyansh Srivastava, Tuomas P. Oikarinen, Tsui-Wei Weng
2023	J	`jnl`	Label-Free Concept Bottleneck Models. CoRR Tuomas P. Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng
2023	A*	`conf`	Label-free Concept Bottleneck Models. ICLR Tuomas P. Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng
2023	A*	`conf`	Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning. ICLR Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng
2023	J	`jnl`	One step closer to unbiased aleatoric uncertainty estimation. CoRR Wang Zhang, Ziwen Martin Ma, Subhro Das, Tsui-Wei Weng, Alexandre Megretski, Luca Daniel, Lam M. Nguyen
2023	J	`jnl`	Prediction without Preclusion: Recourse Verification with Reachable Sets. CoRR Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun
2023	A*	`conf`	Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches. ICDM Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen, Tsui-Wei Weng
2023	J	`jnl`	Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches. CoRR Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen, Tsui-Wei Weng
2023	J	`jnl`	The Importance of Prompt Tuning for Automated Neuron Explanations. CoRR Justin Lee, Tuomas P. Oikarinen, Arjun Chatha, Keng-Chi Chang, Yilan Chen, Tsui-Wei Weng
2022	A*	`conf`	Adversarially Robust Conformal Prediction. ICLR Asaf Gendler, Tsui-Wei Weng, Luca Daniel, Yaniv Romano
2022	J	`jnl`	CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks. CoRR Tuomas P. Oikarinen, Tsui-Wei Weng
2022	J	`jnl`	Evaluating Robustness of Cooperative MARL: A Model-based Approach. CoRR Nhan H. Pham, Lam M. Nguyen, Jie Chen, Hoang Thanh Lam, Subhro Das, Tsui-Wei Weng
2022	—	`conf`	Facile Prediction of Neutrophil Activation State from Microscopy Images: A New Dataset and Comparative Deep Learning Approaches. ISBI Wei Liao, Ching-Yun Ko, Tsui-Wei Weng, Luca Daniel, Joel Voldman
2022	J	`jnl`	Finite-sum smooth optimization with SARAH. Comput. Optim. Appl. Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam
2022	J	`jnl`	Learning Sample Reweighting for Accuracy and Adversarial Robustness. CoRR Chester Holtz, Tsui-Wei Weng, Gal Mishne
2022	A	`conf`	Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier Functions. IROS Zhizhen Qin, Tsui-Wei Weng, Sicun Gao
2022	J	`jnl`	Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier Functions. CoRR Zhizhen Qin, Tsui-Wei Weng, Sicun Gao
2021	J	`jnl`	Fast Training of Provably Robust Neural Networks by SingleProp. CoRR Akhilan Boopathy, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel
2021	A*	`conf`	On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. ICLR Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang
2021	J	`jnl`	On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning. CoRR Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang
2021	A*	`conf`	On the Equivalence between Neural Network and Support Vector Machine. NeurIPS Yilan Chen, Wei Huang, Lam M. Nguyen, Tsui-Wei Weng
2021	J	`jnl`	On the Equivalence between Neural Network and Support Vector Machine. CoRR Yilan Chen, Wei Huang, Lam M. Nguyen, Tsui-Wei Weng
2021	A*	`conf`	Robust Deep Reinforcement Learning through Adversarial Loss. NeurIPS Tuomas P. Oikarinen, Wang Zhang, Alexandre Megretski, Luca Daniel, Tsui-Wei Weng
2020	A*	`conf`	Higher-Order Certification For Randomized Smoothing. NeurIPS Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2020	J	`jnl`	Higher-Order Certification for Randomized Smoothing. CoRR Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2020	J	`jnl`	Rethinking Randomized Smoothing for Adversarial Robustness. CoRR Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Luca Daniel
2020	J	`jnl`	Robust Deep Reinforcement Learning through Adversarial Loss. CoRR Tuomas P. Oikarinen, Tsui-Wei Weng, Luca Daniel
2020	A*	`conf`	Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control. ICLR Tsui-Wei Weng, Krishnamurthy (Dj) Dvijotham, Jonathan Uesato, Kai Xiao, Sven Gowal, Robert Stanforth, Pushmeet Kohli
2020	A*	`conf`	Towards Certificated Model Robustness Against Weight Perturbations. AAAI Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel
2020	A*	`conf`	Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations. CVPR Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2019	A*	`conf`	CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. AAAI Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2019	J	`jnl`	Optimal Finite-Sum Smooth Non-Convex Optimization with SARAH. CoRR Lam M. Nguyen, Marten van Dijk, Dzung T. Phan, Phuong Ha Nguyen, Tsui-Wei Weng, Jayant R. Kalagnanam
2019	J	`jnl`	POPQORN: Quantifying Robustness of Recurrent Neural Networks. CoRR Ching-Yun Ko, Zhaoyang Lyu, Tsui-Wei Weng, Luca Daniel, Ngai Wong, Dahua Lin
2019	A*	`conf`	Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. IJCAI Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin
2019	J	`jnl`	Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. CoRR Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin
2019	J	`jnl`	Towards Verifying Robustness of Neural Networks Against Semantic Perturbations. CoRR Jeet Mohapatra, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2019	J	`jnl`	Verification of Neural Network Control Policy Under Persistent Adversarial Perturbation. CoRR Yuh-Shyang Wang, Tsui-Wei Weng, Luca Daniel
2018	J	`jnl`	CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. CoRR Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
2018	A*	`conf`	Efficient Neural Network Robustness Certification with General Activation Functions. NeurIPS Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel
2018	J	`jnl`	Efficient Neural Network Robustness Certification with General Activation Functions. CoRR Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel
2018	—	`conf`	Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. ICLR (Poster) Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel
2018	J	`jnl`	Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach. CoRR Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel
2018	J	`jnl`	On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm. CoRR Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurélie C. Lozano, Cho-Jui Hsieh, Luca Daniel
2018	—	`conf`	On Extensions of Clever: A Neural Network Robustness Evaluation Algorithm. GlobalSIP Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurélie C. Lozano, Cho-Jui Hsieh, Luca Daniel
2018	J	`jnl`	PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach. CoRR Tsui-Wei Weng, Pin-Yu Chen, Lam M. Nguyen, Mark S. Squillante, Ivan V. Oseledets, Luca Daniel
2018	A*	`conf`	Towards Fast Computation of Certified Robustness for ReLU Networks. ICML Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Luca Daniel, Duane S. Boning, Inderjit S. Dhillon
2018	J	`jnl`	Towards Fast Computation of Certified Robustness for ReLU Networks. CoRR Tsui-Wei Weng, Huan Zhang, Hongge Chen, Zhao Song, Cho-Jui Hsieh, Duane S. Boning, Inderjit S. Dhillon, Luca Daniel
2016	J	`jnl`	A Big-Data Approach to Handle Many Process Variations: Tensor Recovery and Applications. CoRR Zheng Zhang, Tsui-Wei Weng, Luca Daniel
2016	J	`jnl`	A Big-Data Approach to Handle Process Variations: Uncertainty Quantification by Tensor Recovery. CoRR Zheng Zhang, Tsui-Wei Weng, Luca Daniel