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

arXiv:2609.01456 · cs.IR, cs.CL · Submitted 2026-09-01 · Read on arXiv

cs.IR, cs.CL

Submitted: 2026-09-01

Updated: 2026-09-01

Comments: Accepted regular paper at PRICAI 2026. 16 pages, 4 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Alignment — 10× in this paper · explained in 1 episode
• Calibration — 10× in this paper · explained in 7 episodes
• Embeddings — 9× in this paper · explained in 2 episodes
• Grounding — 8× in this paper · explained in 3 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Verification — 4× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Interpretability — 2× in this paper · explained in 15 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• iSEARLE: Improving Textual Inversion for Zero-Shot Composed Image Retrieval
• Soft Filtering: Guiding Zero-shot Composed Image Retrieval with Prescriptive and Proscriptive Constraints
• Training-free Zero-shot Composed Image Retrieval via Weighted Modality Fusion and Similarity

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