REVEAL: A Rubric-Guided Agent for Explicit Evidence Sufficiency Verificationin Long-Video Question Answering
Caijun Yan, Yang Zhou, Meixing Shi, Haoran Sun, Yichen Li, Yuxiang Cai, Yankai Jiang
cs.CV, cs.AI
Submitted: 2026-08-09
Updated: 2026-08-11
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- HealthBench: Evaluating Large Language Models Towards Improved Human Health
- Qwen3-VL Technical Report
- LVAgent: Long Video Understanding by Multi-Round Dynamical Collaboration of MLLM Agents
- CG-Bench: Clue-grounded Question Answering Benchmark for Long Video Understanding
- M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation
- VideoAgent: A Memory-augmented Multimodal Agent for Video Understanding
- SedarEval: Automated Evaluation using Self-Adaptive Rubrics
- Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
- Qworld: Question-Specific Evaluation Criteria for LLMs
- From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
- Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
- A Benchmark for Omni-Modal Reasoning in Long Videos
- RubricHub: A Comprehensive and Highly Discriminative Rubric Dataset via Automated Coarse-to-Fine Generation
- Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
- OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment
- VideoMind: A Chain-of-LoRA Agent for Temporal-Grounded Video Reasoning
- Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
- RIFT: A RubrIc Failure Mode Taxonomy and Automated Diagnostics
- Qwen3.5-Omni Technical Report
- Proximal Policy Optimization Algorithms
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