Think Thrice Before Reranking: Multi-perspective Evidence and Reasoning Integration for Text Reranking

Excerpt

arXiv:2609.20131v1 Announce Type: cross Abstract: Reasoning-based reranking with Large Language Models (LLMs) has shown promising improvements in text ranking. However, current methods predominantly rely on a single reasoning trajectory, resulting in rankings that are susceptible to reasoning errors and inherently constrained in modeling the multifaceted signals underlying document relevance. To resolve this dilemma, we propose MERIT-Rank(Multi-perspective Evidence and Reasoning Integration for