作者位次 #6/7ICLR 2026Poster· Reinforcement Learning / Deep RL
Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning
Ke Sun · Hongming Zhang · Jun Jin · Chao Gao · Xi Chen · Wulong Liu · Linglong Kong
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Ke Sun · Hongming Zhang · Jun Jin · Chao Gao · Xi Chen · Wulong Liu · Linglong Kong
Weizhe Lin · Xing Li · Zhiyuan Yang · Xiaojin Fu · Huiling Zhen · Yaoyuan Wang · Xianzhi Yu · Wulong Liu · Xiaosong Li · Mingxuan Yuan
Zehua Pei · Hui-Ling Zhen · Lancheng Zou · Xianzhi Yu · Wulong Liu · Sinno Jialin Pan · Mingxuan Yuan · Bei Yu
Scaling large language models (LLMs) improves performance but significantly increases inference costs, with feed-forward networks (FFNs) consuming the majority of computational resources. While Mixture-of-Experts (MoE) architectures can reduce this cost through sparse activation, restructuring ex...