arXiv (All)
open access
From Transformation to Target State: Rethinking Query Representation for Zero-Shot Composed Image Retrieval
Composed image retrieval (CIR) aims to retrieve a desired target image from a query consisting of a reference image and a modification text. This task exhibits an unusual representational asymmetry: the modification text specifies a transition from the reference state, whereas retrieval candidates d
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Personalizing retrieval using joint embeddings; or "The Return of Fluffy"#219331
- Autoregressive Retriever: Improving Query Understanding from Item Feedback for Universal Multimodal Retrieval#1248946
- Concepts Complement Dense Semantics: Learning Compact Sparse Spaces for Text-Image Retrieval#1117002
- RAGSieve: Self-Referenced Local Contrast for Knowledge-Poison Detection in Retrieval-Augmented Generation#985209
- Who Remains, What Changes: Identity Anchored Composed Gait Retrieval#819472
Record · ID 1202412
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive