attribute matching 1composed image retrieval 1llm reranking 1vision-free retrieval 1zero-shot learning 1
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cs.CV2026
Towards Vision-Free CIR: Attribute-Augmented Scoring and LLM-Based Reranking for Zero-Shot Composed Image Retrieval
Ryotaro Shimada, Yu-Chieh Lin, Yuji Nozawa +3
The paper proposes a vision‑free framework for composed image retrieval that uses attribute‑augmented scoring to recover visual details and a large language model for reranking to…
cs.CV2026
CIRCLED: A Multi-turn CIR Dataset with Consistent Dialogues across Domains
Tomohisa Takeda, Yu-Chieh Lin, Yuji Nozawa +3
Existing Multi-Turn Composed Image Retrieval (MTCIR) datasets lack dialogue-historyconsistency and are restricted to the fashion domain. To address these limitations, we construct…
cs.CV2024
SVGEditBench: A Benchmark Dataset for Quantitative Assessment of LLM's SVG Editing Capabilities
Kunato Nishina, Yusuke Matsui
Text-to-image models have shown progress in recent years. Along with this progress, generating vector graphics from text has also advanced. SVG is a popular format for vector graph…