UniME-R1：基于硬负样本的检索中心思维链统一多模态检索

AI 摘要

本文提出UniME-R1框架，用于统一多模态检索。该框架通过嵌入器-顾问架构，基于初始检索结果生成检索中心思维链（RC-CoT），以解决LVLM检索器忽略细粒度判别线索的问题。实验表明，UniME-R1在MMEB-V2等多个基准上优于强基线。

正文节选

Learning from Failures: Retrieval-Centric CoT via Hard Negatives for Unified Multimodal Retrieval Abstract Unified multimodal retrieval aims to identify candidates that satisfy complex user intent expressed through heterogeneous inputs. Although Large Vision-Language Model (LVLM)-based retrievers are efficient and scalable, directly encoding raw multimodal inputs often misses fine-grained discriminative cues, leading to confusion among semantically similar candidates. Recent methods mitigate thi

发布时间：—

抓取时间：2026-08-07 10:12

来源机构：Hugging Face