most citedZero-Shot Multi-Hop Question Answering via Monte-Carlo Tree Search with Large Language Models

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cs.CL2025

QUPID: Quantified Understanding for Enhanced Performance, Insights, and Decisions in Korean Search Engines

Ohjoon Kwon, Changsu Lee, Jihye Back +3

Large language models (LLMs) have been widely used for relevance assessment in information retrieval. However, our study demonstrates that combining two distinct small language mod…

cs.CL2024★ 1 cited

Zero-Shot Multi-Hop Question Answering via Monte-Carlo Tree Search with Large Language Models

Seongmin Lee, Jaewook Shin, Youngjin Ahn +3

Recent advances in large language models (LLMs) have significantly impacted the domain of multi-hop question answering (MHQA), where systems are required to aggregate information a…