arXiv (All)
open access
Image Recognition with Vision and Language Embeddings of VLMs
Vision-language models (VLMs) have enabled strong zero-shot classification through image-text alignment. Yet, their purely visual inference capabilities remain under-explored. In this work, we conduct a comprehensive evaluation of both language-guided and vision-only image classification with a dive
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
- VLM4Cluster: Benchmarking Deep Clustering In the Era of Vision-Language Pre-training#1131849
- Topology-Aware Representation Alignment for Semi-Supervised Vision-Language Learning#1354893
- An overview of 3D Vision-Language Models#972638
- Focus Where It Counts: A Salience-Driven Vision-Language Model for Low Vision Assistance#784969
- Focus Where It Counts: A Salience-Driven Vision-Language Model for Low Vision Assistance#783379
Record · ID 1248289
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