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cs.LG2024
SPO: Multi-Dimensional Preference Sequential Alignment With Implicit Reward Modeling
Xingzhou Lou, Junge Zhang, Jian Xie +3
Human preference alignment is critical in building powerful and reliable large language models (LLMs). However, current methods either ignore the multi-dimensionality of human pref…
cs.LG2024
Safe Reinforcement Learning with Free-form Natural Language Constraints and Pre-Trained Language Models
Xingzhou Lou, Junge Zhang, Ziyan Wang +2
Safe reinforcement learning (RL) agents accomplish given tasks while adhering to specific constraints. Employing constraints expressed via easily-understandable human language offe…
cs.LG2021
Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning
Wenzhen Huang, Qiyue Yin, Junge Zhang +1
Model-based reinforcement learning (RL) is more sample efficient than model-free RL by using imaginary trajectories generated by the learned dynamics model. When the model is inacc…