arXiv (All)
open access
PlaylistEval: Can Video-Language Judges Be Trusted at Day Scale and Beyond?
Video-language models are increasingly used as judges of video understanding, both for evaluating model outputs and for training reward models. Whether their judgments remain reliable when the evidence is buried in day-long videos has yet to be established. Existing benchmarks cannot answer this. Th
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
- Rigel: Self-Distilled Score Adaptation for Image and Video Captioning Evaluation#1109090
- Beyond Binary Preferences: Graded Preference Optimization for Limb-Motion Captioning#1131829
- Grounded Checklist Partial Credit for Agent Skill Trajectories#780804
- Grounded Checklist Partial Credit for Agent Skill Trajectories#779429
- Target-Checked Reliability Score Refinement for Video Question Answering#1071092
Record · ID 1119387
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