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cs.LG2024
DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints
Andrew Zhao, Quentin Xu, Matthieu Lin +4
Recent advances in large language model assistants have made them indispensable, raising significant concerns over managing their safety. Automated red teaming offers a promising a…
cs.LG2024
Exploring Text-to-Motion Generation with Human Preference
Jenny Sheng, Matthieu Lin, Andrew Zhao +5
This paper presents an exploration of preference learning in text-to-motion generation. We find that current improvements in text-to-motion generation still rely on datasets requir…
cs.LG2023★ 1 cited
Augmenting Unsupervised Reinforcement Learning with Self-Reference
Andrew Zhao, Erle Zhu, Rui Lu +3
Humans possess the ability to draw on past experiences explicitly when learning new tasks and applying them accordingly. We believe this capacity for self-referencing is especially…