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2024/11/21 2

Technical Report: Enhancing LLM Reasoning with Reward-guided Tree Search

https://arxiv.org/abs/2411.11694 Technical Report: Enhancing LLM Reasoning with Reward-guided Tree SearchRecently, test-time scaling has garnered significant attention from the research community, largely due to the substantial advancements of the o1 model released by OpenAI. By allocating more computational resources during the inference phase, large languagarxiv.orgRecently, test-time scaling ..

카테고리 없음 2024.11.21

Is Your LLM Secretly a World Model of the Internet?MODEL-BASED PLANNING FOR WEB AGENTS

https://arxiv.org/pdf/2411.06559Language agents have demonstrated promising capabilities in automating webbased tasks, though their current reactive approaches still underperform largely compared to humans. While incorporating advanced planning algorithms, particularly tree search methods, could enhance these agents' performance, implementing tree search directly on live websites poses significa..

카테고리 없음 2024.11.21
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  • 분류 전체보기 (287)
    • inference-time, RLHF (41)
      • STaR, ReST (4)
      • STaR, ResT - LMM (17)
      • search (language) (10)
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    • 한계 limitation (1)
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    • 3D, real world, game, VR (2)

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