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cs.CL2026
Rethinking Soft Compression in Retrieval-Augmented Generation: A Query-Conditioned Selector Perspective
Yunhao Liu, Zian Jia, Xinyu Gao +2
Retrieval-Augmented Generation (RAG) effectively grounds Large Language Models (LLMs) with external knowledge and is widely applied to Web-related tasks. However, its scalability i…
cs.AI2026
RAPO: Expanding Exploration for LLM Agents via Retrieval-Augmented Policy Optimization
Siwei Zhang, Yun Xiong, Xi Chen +4
Agentic Reinforcement Learning (Agentic RL) has shown remarkable potential in large language model-based (LLM) agents. These works can empower LLM agents to tackle complex tasks vi…