From the 1 of 5 linked papers with an AI index.
5 papers
HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation
Shaopeng Zhai, Qi Zhang, Tianyi Zhang +5
The paper introduces HELP, a pipeline that uses two specialized human operators to supervise a fleet of robots during post‑training of Vision‑Language‑Action models, improving huma…
Affordance2Action: Task-Conditioned Scene-level Affordance Grounding for Real-Time Manipulation
Litao Liu, Yifan Han, Pengfei Yi +9
Task-conditioned manipulation requires grounding instructions to task-relevant functional parts rather than object categories. This setting is scene-dependent and often one-to-many…
Preserving Foundational Capabilities in Flow-Matching VLAs through Conservative SFT
Tianyi Zhang, Shaopeng Zhai, Haoran Zhang +2
Unconstrained fine-tuning of flow-matching Vision-Language-Action (VLA) models drives dense parameter overwrites, degrading pre-trained capabilities. We present Conservative Superv…
Neural Video Compression with Domain Transfer
Tiange Zhang, Rongqun Lin, Xiandong Meng +4
Content-adaptive compression has always been a key direction in neural video coding (NVC), aiming to mitigate the domain gap between training and testing data. Such gaps often aris…
A Vision-Language-Action-Critic Model for Robotic Real-World Reinforcement Learning
Shaopeng Zhai, Qi Zhang, Tianyi Zhang +7
Robotic real-world reinforcement learning (RL) with vision-language-action (VLA) models is bottlenecked by sparse, handcrafted rewards and inefficient exploration. We introduce VLA…