Weng, Tsui-Wei

40 publications

ICLR 2025 Concept Bottleneck Large Language Models Chung-En Sun, Tuomas Oikarinen, Berk Ustun, Tsui-Wei Weng

ICML 2025 Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Tuomas Oikarinen, Ge Yan, Tsui-Wei Weng

CVPR 2025 Interpretable Generative Models Through Post-Hoc Concept Bottlenecks Akshay Kulkarni, Ge Yan, Chung-En Sun, Tuomas Oikarinen, Tsui-Wei Weng

TMLR 2025 Interpreting Neurons in Deep Vision Networks with Language Models Nicholas Bai, Rahul Ajay Iyer, Tuomas Oikarinen, Akshay R. Kulkarni, Tsui-Wei Weng

WACV 2025 SAND: Enhancing Open-Set Neuron Descriptions Through Spatial Awareness Anvita Agarwal Srinivas, Tuomas Oikarinen, Divyansh Srivastava, Wei-Hung Weng, Tsui-Wei Weng

ICML 2025 Understanding Fixed Predictions via Confined Regions Connor Lawless, Tsui-Wei Weng, Berk Ustun, Madeleine Udell

ICML 2024 AND: Audio Network Dissection for Interpreting Deep Acoustic Models Tung-Yu Wu, Yu-Xiang Lin, Tsui-Wei Weng

NeurIPS 2024 Abstracted Shapes as Tokens - A Generalizable and Interpretable Model for Time-Series Classification Yunshi Wen, Tengfei Ma, Tsui-Wei Weng, Lam M. Nguyen, Anak Agung Julius

ICML 2024 Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents Chung-En Sun, Sicun Gao, Tsui-Wei Weng

TMLR 2024 Concept-Driven Continual Learning Sin-Han Yang, Tuomas Oikarinen, Tsui-Wei Weng

ICMLW 2024 Crafting Large Language Models for Enhanced Interpretability Chung-En Sun, Tuomas Oikarinen, Tsui-Wei Weng

ICMLW 2024 Describe-and-Dissect: Interpreting Neurons in Vision Networks with Language Models Nicholas Bai, Rahul Ajay Iyer, Tuomas Oikarinen, Tsui-Wei Weng

ECCV 2024 Interpretability-Guided Test-Time Adversarial Defense Akshay Kulkarni, Tsui-Wei Weng

ICML 2024 Linear Explanations for Individual Neurons Tuomas Oikarinen, Tsui-Wei Weng

ICLR 2024 Prediction Without Preclusion: Recourse Verification with Reachable Sets Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng, Berk Ustun

NeurIPS 2024 Probabilistic Federated Prompt-Tuning with Non-IID and Imbalanced Data Pei-Yau Weng, Minh Hoang, Lam M. Nguyen, My T. Thai, Tsui-Wei Weng, Trong Nghia Hoang

NeurIPS 2024 Provable and Efficient Dataset Distillation for Kernel Ridge Regression Yilan Chen, Wei Huang, Tsui-Wei Weng

ICLR 2024 Provably Robust Conformal Prediction with Improved Efficiency Ge Yan, Yaniv Romano, Tsui-Wei Weng

NeurIPS 2024 VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance Divyansh Srivastava, Ge Yan, Tsui-Wei Weng

TMLR 2023 Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection Wei Huang, Chunrui Liu, Yilan Chen, Richard Yi Da Xu, Miao Zhang, Tsui-Wei Weng

ICLR 2023 CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks Tuomas Oikarinen, Tsui-Wei Weng

ICML 2023 ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen

ICCV 2023 Corrupting Neuron Explanations of Deep Visual Features Divyansh Srivastava, Tuomas Oikarinen, Tsui-Wei Weng

NeurIPSW 2023 Fooling GPT with Adversarial In-Context Examples for Text Classification Sudhanshu Ranjan, Chung-En Sun, Linbo Liu, Tsui-Wei Weng

ICLR 2023 Label-Free Concept Bottleneck Models Tuomas Oikarinen, Subhro Das, Lam M. Nguyen, Tsui-Wei Weng

ICLR 2023 Min-Max Multi-Objective Bilevel Optimization with Applications in Robust Machine Learning Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng

ICMLW 2022 Fast Convergence for Unstable Reinforcement Learning Problems by Logarithmic Mapping Wang Zhang, Lam M. Nguyen, Subhro Das, Alexandre Megretski, Luca Daniel, Tsui-Wei Weng

ICLR 2022 Adversarially Robust Conformal Prediction Asaf Gendler, Tsui-Wei Weng, Luca Daniel, Yaniv Romano

ICLRW 2022 CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks Tuomas Oikarinen, Tsui-Wei Weng

ICLRW 2022 Robust Randomized Smoothing via Two Cost-Effective Approaches Linbo Liu, Trong Nghia Hoang, Lam M. Nguyen, Tsui-Wei Weng

ICLR 2021 On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning Ren Wang, Kaidi Xu, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang

NeurIPS 2021 On the Equivalence Between Neural Network and Support Vector Machine Yilan Chen, Wei Huang, Lam Nguyen, Tsui-Wei Weng

NeurIPS 2021 Robust Deep Reinforcement Learning Through Adversarial Loss Tuomas Oikarinen, Wang Zhang, Alexandre Megretski, Luca Daniel, Tsui-Wei Weng

NeurIPS 2020 Higher-Order Certification for Randomized Smoothing Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

ICLR 2020 Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control Tsui-Wei Weng, Krishnamurthy Dvijotham, Jonathan Uesato, Kai Xiao, Sven Gowal, Robert Stanforth, Pushmeet Kohli

AAAI 2020 Towards Certificated Model Robustness Against Weight Perturbations Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel

AAAI 2019 CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

IJCAI 2019 Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin

NeurIPS 2018 Efficient Neural Network Robustness Certification with General Activation Functions Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, Luca Daniel

ICLR 2018 Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel