| A semantic loss function for deep learning with symbolic knowledge J Xu, Z Zhang, T Friedman, Y Liang, G Broeck International conference on machine learning, 5502-5511, 2018 | 487 | 2018 |
| Describe, explain, plan and select: interactive planning with LLMs enables open-world multi-task agents Z Wang, S Cai, G Chen, A Liu, XS Ma, Y Liang Advances in Neural Information Processing Systems 36, 2024 | 191* | 2024 |
| Horizon: Facebook's open source applied reinforcement learning platform J Gauci, E Conti, Y Liang, K Virochsiri, Y He, Z Kaden, V Narayanan, X Ye, ... arXiv preprint arXiv:1811.00260, 2018 | 155 | 2018 |
| State of the art control of atari games using shallow reinforcement learning Y Liang, MC Machado, E Talvitie, M Bowling arXiv preprint arXiv:1512.01563, 2015 | 138 | 2015 |
| Learning the structure of probabilistic sentential decision diagrams Y Liang, J Bekker, G Van den Broeck Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence …, 2017 | 108 | 2017 |
| Learning logistic circuits Y Liang, G Van den Broeck Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4277-4286, 2019 | 57 | 2019 |
| What to expect of classifiers? reasoning about logistic regression with missing features P Khosravi, Y Liang, YJ Choi, GV Broeck arXiv preprint arXiv:1903.01620, 2019 | 49 | 2019 |
| On tractable computation of expected predictions P Khosravi, YJ Choi, Y Liang, A Vergari, G Van den Broeck Advances in Neural Information Processing Systems 32, 2019 | 49 | 2019 |
| Sqa3d: Situated question answering in 3d scenes X Ma, S Yong, Z Zheng, Q Li, Y Liang, SC Zhu, S Huang arXiv preprint arXiv:2210.07474, 2022 | 46 | 2022 |
| Sam: Squeeze-and-mimic networks for conditional visual driving policy learning A Zhao, T He, Y Liang, H Huang, G Van den Broeck, S Soatto Conference on Robot Learning, 156-175, 2021 | 36* | 2021 |
| ProAgent: building proactive cooperative agents with large language models C Zhang, K Yang, S Hu, Z Wang, G Li, Y Sun, C Zhang, Z Zhang, A Liu, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (16), 17591 …, 2024 | 31* | 2024 |
| Handling missing data in decision trees: A probabilistic approach P Khosravi, A Vergari, YJ Choi, Y Liang, GV Broeck arXiv preprint arXiv:2006.16341, 2020 | 31 | 2020 |
| Inference aided reinforcement learning for incentive mechanism design in crowdsourcing Z Hu, Y Liang, J Zhang, Z Li, Y Liu Advances in Neural Information Processing Systems 31, 2018 | 29 | 2018 |
| Large language models are in-context semantic reasoners rather than symbolic reasoners X Tang, Z Zheng, J Li, F Meng, SC Zhu, Y Liang, M Zhang arXiv preprint arXiv:2305.14825, 2023 | 27 | 2023 |
| Juice: A julia package for logic and probabilistic circuits M Dang, P Khosravi, Y Liang, A Vergari, G Van den Broeck Proceedings of the AAAI Conference on Artificial Intelligence 35 (18), 16020 …, 2021 | 27 | 2021 |
| Jarvis-1: Open-world multi-task agents with memory-augmented multimodal language models Z Wang, S Cai, A Liu, Y Jin, J Hou, B Zhang, H Lin, Z He, Z Zheng, Y Yang, ... arXiv preprint arXiv:2311.05997, 2023 | 26 | 2023 |
| Open-world multi-task control through goal-aware representation learning and adaptive horizon prediction S Cai, Z Wang, X Ma, A Liu, Y Liang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 22 | 2023 |
| Unifying Probabilistic Reasoning, Learning, and Classification with Circuit Representations Y Liang University of California, Los Angeles, 2021 | 20* | 2021 |
| Groot: Learning to follow instructions by watching gameplay videos S Cai, B Zhang, Z Wang, X Ma, A Liu, Y Liang arXiv preprint arXiv:2310.08235, 2023 | 11 | 2023 |
| Efficient meta reinforcement learning for preference-based fast adaptation Z Ren, A Liu, Y Liang, J Peng, J Ma Advances in Neural Information Processing Systems 35, 15502-15515, 2022 | 7 | 2022 |
Guy Van den BroeckAssociate Professor and Samueli Fellow, UCLAVerified email at cs.ucla.edu
