arXiv (All)
open access
Chehre: An Emoji-Prompted Dataset to Explore Perceptual Flexibility in Video Language Models
Do people perceive the same facial expression in the same way? Should we expect vision models to be flexible in how they perceive facial expressions? Facial expressions are nonverbal social signals used in human interaction, but facial expression recognition datasets often focus on a single determin
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
- Chehre: An Emoji-Prompted Dataset to Explore Perceptual Flexibility in Video Language Models#920950
- Verbal and facial expression cues in emotional alignment.#284940
- Personalized Korean Lipreading as Visual Speech Recognition: Transfer, Census and Adaptation on OLKAVS#1076644
- Frontier vision-language models have overtaken young adults at detecting AI-generated portraits -- but not their calibration#799430
- Frontier vision-language models have overtaken young adults at detecting AI-generated portraits -- but not their calibration#798007
Record · ID 925185
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