Hong, Zhang-Wei

29 publications

ICLR 2025 ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization Chen Bo Calvin Zhang, Zhang-Wei Hong, Aldo Pacchiano, Pulkit Agrawal

NeurIPS 2025 RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning Kaiwen Zha, Zhengqi Gao, Maohao Shen, Zhang-Wei Hong, Duane S Boning, Dina Katabi

ICLR 2025 ReGen: Generative Robot Simulation via Inverse Design Phat Tan Nguyen, Tsun-Hsuan Wang, Zhang-Wei Hong, Erfan Aasi, Andrew Silva, Guy Rosman, Sertac Karaman, Daniela Rus

ICML 2025 Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search Maohao Shen, Guangtao Zeng, Zhenting Qi, Zhang-Wei Hong, Zhenfang Chen, Wei Lu, Gregory W. Wornell, Subhro Das, David Daniel Cox, Chuang Gan

NeurIPSW 2024 Curiosity-Driven Red Teaming for Large Language Models Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James R. Glass, Akash Srivastava, Pulkit Agrawal

ICLR 2024 Curiosity-Driven Red-Teaming for Large Language Models Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James R. Glass, Akash Srivastava, Pulkit Agrawal

NeurIPS 2024 Going Beyond Heuristics by Imposing Policy Improvement as a Constraint Chi-Chang Lee, Zhang-Wei Hong, Pulkit Agrawal

TMLR 2024 Grid Cell-Inspired Fragmentation and Recall for Efficient mAP Building Jaedong Hwang, Zhang-Wei Hong, Eric R Chen, Akhilan Boopathy, Pulkit Agrawal, Ila R Fiete

NeurIPSW 2024 Grid Cell-Inspired Fragmentation and Recall for Efficient mAP Building Jaedong Hwang, Zhang-Wei Hong, Eric R Chen, Akhilan Boopathy, Pulkit Agrawal, Ila R Fiete

NeurIPSW 2024 ImageNet-RIB Benchmark: Large Pre-Training Datasets Don't Guarantee Robustness After Fine-Tuning Jaedong Hwang, Brian Cheung, Zhang-Wei Hong, Akhilan Boopathy, Pulkit Agrawal, Ila R Fiete

ICMLW 2024 ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization Chen Bo Calvin Zhang, Zhang-Wei Hong, Aldo Pacchiano, Pulkit Agrawal

ICML 2024 Random Latent Exploration for Deep Reinforcement Learning Srinath V. Mahankali, Zhang-Wei Hong, Ayush Sekhari, Alexander Rakhlin, Pulkit Agrawal

NeurIPSW 2024 Red Teaming Language-Conditioned Robot Models via Vision Language Models Sathwik Karnik, Zhang-Wei Hong, Nishant Abhangi, Yen-Chen Lin, Tsun-Hsuan Wang, Pulkit Agrawal

NeurIPS 2023 Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets Zhang-Wei Hong, Aviral Kumar, Sathwik Karnik, Abhishek Bhandwaldar, Akash Srivastava, Joni K. Pajarinen, Romain Laroche, Abhishek Gupta, Pulkit Agrawal

ICLR 2023 Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting Zhang-Wei Hong, Pulkit Agrawal, Remi Tachet des Combes, Romain Laroche

L4DC 2023 Model Predictive Control via On-Policy Imitation Learning Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie

NeurIPSW 2023 Neuro-Inspired Fragmentation and Recall to Overcome Catastrophic Forgetting in Curiosity Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy, Pulkit Agrawal, Ila Fiete

ICML 2023 Parallel $q$-Learning: Scaling Off-Policy Reinforcement Learning Under Massively Parallel Simulation Zechu Li, Tao Chen, Zhang-Wei Hong, Anurag Ajay, Pulkit Agrawal

ICML 2023 TGRL: An Algorithm for Teacher Guided Reinforcement Learning Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal

ICLRW 2023 TGRL: Teacher Guided Reinforcement Learning Algorithm for POMDPs Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal

ICLR 2022 Bi-Linear Value Networks for Multi-Goal Reinforcement Learning Zhang-Wei Hong, Ge Yang, Pulkit Agrawal

NeurIPS 2022 Redeeming Intrinsic Rewards via Constrained Optimization Eric Chen, Zhang-Wei Hong, Joni K. Pajarinen, Pulkit Agrawal

ICLR 2022 Topological Experience Replay Zhang-Wei Hong, Tao Chen, Yen-Chen Lin, Joni Pajarinen, Pulkit Agrawal

ECML-PKDD 2021 Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning Zhang-Wei Hong, Prabhat Nagarajan, Guilherme Maeda

CoRL 2019 Adversarial Active Exploration for Inverse Dynamics Model Learning Zhang-Wei Hong, Tsu-Jui Fu, Tzu-Yun Shann, Chun-Yi Lee

NeurIPS 2018 Diversity-Driven Exploration Strategy for Deep Reinforcement Learning Zhang-Wei Hong, Tzu-Yun Shann, Shih-Yang Su, Yi-Hsiang Chang, Tsu-Jui Fu, Chun-Yi Lee

IJCAI 2018 Virtual-to-Real: Learning to Control in Visual Semantic Segmentation Zhang-Wei Hong, Yu-Ming Chen, Hsuan-Kung Yang, Shih-Yang Su, Tzu-Yun Shann, Yi-Hsiang Chang, Brian Hsi-Lin Ho, Chih-Chieh Tu, Tsu-Ching Hsiao, Hsin-Wei Hsiao, Sih-Pin Lai, Yueh-Chuan Chang, Chun-Yi Lee

ICLR 2017 Tactics of Adversarial Attack on Deep Reinforcement Learning Agents Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao, Meng-Li Shih, Ming-Yu Liu, Min Sun

IJCAI 2017 Tactics of Adversarial Attack on Deep Reinforcement Learning Agents Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao, Meng-Li Shih, Ming-Yu Liu, Min Sun