4 citations · 5 across the 4 of their papers we have counts for
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cs.AI2024
SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement
Antonis Antoniades, Albert Örwall, Kexun Zhang +3
Software engineers operating in complex and dynamic environments must continuously adapt to evolving requirements, learn iteratively from experience, and reconsider their approache…
cs.AI2024★ 4 cited
Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning
Yuxi Xie, Anirudh Goyal, Wenyue Zheng +4
We introduce an approach aimed at enhancing the reasoning capabilities of Large Language Models (LLMs) through an iterative preference learning process inspired by the successful s…