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cs.CV2026
FIRM-Video: Check Before You Score for Reliable Text-to-Video Reward Modeling
Peiyuan Zhang, Xiangyu Zhao, Hongbo Liu +8
Reliable reward models are essential for text-to-video evaluation and alignment. However, the trade-off between evaluation accuracy and inference efficiency places high demands on…
cs.CV2025
VITA-VLA: Efficiently Teaching Vision-Language Models to Act via Action Expert Distillation
Shaoqi Dong, Chaoyou Fu, Haihan Gao +12
Vision-Language Action (VLA) models significantly advance robotic manipulation by leveraging the strong perception capabilities of pretrained vision-language models (VLMs). By inte…
cs.CV2024
Prompt-based Visual Alignment for Zero-shot Policy Transfer
Haihan Gao, Rui Zhang, Qi Yi +13
Overfitting in RL has become one of the main obstacles to applications in reinforcement learning(RL). Existing methods do not provide explicit semantic constrain for the feature ex…