PlaylistEval: Can Video-Language Judges Be Trusted at Day Scale and Beyond?
cs.CV, cs.AI, cs.CL
Submitted: 2026-09-28
Updated: 2026-09-28
Terminology
Sources
- Gemma 4 Technical Report
- Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
- Neptune: The Long Orbit to Benchmarking Long Video Understanding
- Qwen3-ASR Technical Report
- Skywork-VL Reward: An Effective Reward Model for Multimodal Understanding and Reasoning
- Video Understanding Reward Modeling: A Robust Benchmark and Performant Reward Models
- Qwen3-Omni Technical Report
- Omni-Embed-Nemotron: A Unified Multimodal Retrieval Model for Text, Image, Audio, and Video
- Multimodal RewardBench: Holistic Evaluation of Reward Models for Vision Language Models
- VideoRewardBench: Comprehensive Evaluation of Multimodal Reward Models for Video Understanding
- WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report
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