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cs.AI2025
Unlocking the Power of Multi-Agent LLM for Reasoning: From Lazy Agents to Deliberation
Zhiwei Zhang, Xiaomin Li, Yudi Lin +8
Large Language Models (LLMs) trained with reinforcement learning and verifiable rewards have achieved strong results on complex reasoning tasks. Recent work extends this paradigm t…
cs.AI2025
A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applications
Minhua Lin, Zongyu Wu, Zhichao Xu +6
The advent of large language models (LLMs) has transformed information access and reasoning through open-ended natural language interaction. However, LLMs remain limited by static…
cs.AI2025
How Far are LLMs from Real Search? A Comprehensive Study on Efficiency, Completeness, and Inherent Capabilities
Minhua Lin, Hui Liu, Xianfeng Tang +7
Search plays a fundamental role in problem-solving across various domains, with most real-world decision-making problems being solvable through systematic search. Drawing inspirati…