| Fairedit: Preserving fairness in graph neural networks through greedy graph editing D Loveland, J Pan, AF Bhathena, Y Lu arXiv, 2022, 2022 | 21 | 2022 |
| Data-Efficient Learning of Natural Language to Linear Temporal Logic Translators for Robot Task Specification J Pan, G Chou, D Berenson ICRA 2023, 2023 | 18 | 2023 |
| Inversion-Free Image Editing with Natural Language S Xu, Y Huang, J Pan, Z Ma, J Chai CVPR 2024, 2023 | 13 | 2023 |
| Danli: Deliberative agent for following natural language instructions Y Zhang, J Yang, J Pan, S Storks, N Devraj, Z Ma, KP Yu, Y Bao, J Chai EMNLP (Oral) 2022, 2022 | 9 | 2022 |
| Autonomous Evaluation and Refinement of Digital Agents J Pan, Y Zhang, N Tomlin, Y Zhou, S Levine, A Suhr arXiv, 2024, 2024 | 8 | 2024 |
| World-to-Words: Grounded Open Vocabulary Acquisition through Fast Mapping in Vision-Language Models Z Ma, J Pan, J Chai ACL (Outstanding Paper Award) 2023, 2023 | 8 | 2023 |
| ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL Y Zhou, A Zanette, J Pan, S Levine, A Kumar ICML 2024, 2024 | 7 | 2024 |
| Grounding Visual Illusions in Language: Do Vision-Language Models Perceive Illusions Like Humans? Y Zhang, J Pan, Y Zhou, R Pan, J Chai EMNLP 2023, 2023 | 6 | 2023 |
| Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning Y Zhai, H Bai, Z Lin, J Pan, S Tong, Y Zhou, A Suhr, S Xie, Y LeCun, Y Ma, ... arXiv preprint arXiv:2405.10292, 2024 | 5 | 2024 |
| SEAGULL: An Embodied Agent for Instruction Following through Situated Dialog Y Zhang, J Yang, K Yu, Y Dai, S Storks, Y Bao, J Pan, N Devraj, Z Ma, ... Alexa Prize SimBot Challenge Proceedings (Champion), 2023 | 2 | 2023 |
| DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning H Bai, Y Zhou, M Cemri, J Pan, A Suhr, S Levine, A Kumar arXiv preprint arXiv:2406.11896, 2024 | 1 | 2024 |
| Autonomous Evaluation and Refinement of Web Agents J Pan, YZNTY Zhou, S Levine, A Suhr | | |
| DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning Y Zhou, H Bai, M Cemri, J Pan, A Suhr, S Levine, A Kumar Automated Reinforcement Learning: Exploring Meta-Learning, AutoML, and LLMs, 0 | | |
