AutoConcept: Training-Free Concept-Guided Reranking for Metadata-Available Composed Image Retrieval

Paper recorded by Signals 4 on 2026-09-01 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-01 on arXiv · recorded by Signals 4 on 2026-09-02

Category: cs.CL · 自然语言处理 · first seen 2026-09-02

Abstract

Composed image retrieval (CIR) retrieves a target image from a reference image and a text modification. This paper studies metadata-available CIR reranking, where a fixed CIR model first returns a candidate pool and gallery metadata is then used for second-stage concept-guided scoring. We introduce AutoConcept, a training-free reranker that converts concept evidence into an interpretable memory. A

Read on arXiv →