dense reward learning 1failure synthesis 1reinforcement learning 1robotic manipulation 1vision-language models 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.RO2026
DenseReward: Dense Reward Learning via Failure Synthesis for Robotic Manipulation
Yu Fang, Wanxi Dong, Jiaqi Liu +7
The paper presents DenseReward, a dense visual‑language reward model for robotic manipulation that is trained on automatically synthesized failure trajectories in simulation, enabl…
cs.RO2026
VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing
Yixiao Wang, Mingxiao Huo, Zhixuan Liang +8
Pretrained vision foundation models (VFMs) advance robotic learning via rich visual representations, yet individual VFMs typically excel only in specific domains, limiting generali…
cs.CL2025
Spec-LLaVA: Accelerating Vision-Language Models with Dynamic Tree-Based Speculative Decoding
Mingxiao Huo, Jiayi Zhang, Hewei Wang +4
Vision-Language Models (VLMs) enable powerful multimodal reasoning but suffer from slow autoregressive inference, limiting their deployment in real-time applications. We introduce…