2 citations · 2 across the 11 of their papers we have counts for
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cs.AI2024
Preference Goal Tuning: Post-Training as Latent Control for Frozen Policies
Guangyu Zhao, Kewei Lian, Haoxuan Ru +8
Goal-conditioned policies enable decision-making models to execute diverse behaviors based on specified goals, yet their downstream performance is often highly sensitive to the cho…
cs.AI2024★ 2 cited
Enhance Reasoning for Large Language Models in the Game Werewolf
Shuang Wu, Liwen Zhu, Tao Yang +4
This paper presents an innovative framework that integrates Large Language Models (LLMs) with an external Thinker module to enhance the reasoning capabilities of LLM-based agents.…
cs.AI2024
Not All Tasks Are Equally Difficult: Multi-Task Deep Reinforcement Learning with Dynamic Depth Routing
Jinmin He, Kai Li, Yifan Zang +4
Multi-task reinforcement learning endeavors to accomplish a set of different tasks with a single policy. To enhance data efficiency by sharing parameters across multiple tasks, a c…