VL-RewardBench

Dataset Card for VLRewardBench Project Page: https://vl-rewardbench.github.io Dataset Summary VLRewardBench is a comprehensive benchmark designed to evaluate vision-language generative reward models (VL-GenRMs) across visual perception, hallucination detection, and reasoning tasks. The benchmark contains 1,250 high-qua

Papers using VL-RewardBench (7)

DeltaRubric: Generative Multimodal Reward Modeling via Joint Planning and Verification2026Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling2026MSRL: Scaling Generative Multimodal Reward Modeling via Multi-Stage Reinforcement Learning2026Self-Improving VLM Judges Without Human Annotations2025Skywork-VL Reward: An Effective Reward Model for Multimodal Understanding and Reasoning2025From Captions to Rewards (CAREVL): Leveraging Large Language Model Experts for Enhanced Reward Modeling in Large Vision-Language Models2025VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models2024 · 2 cites