ViVa: A Video-Generative Value Model for Robot Reinforcement Learning
Paper • 2604.08168 • Published • 17
AI & ML interests
None defined yet.
Recent Activity
View all activity
Papers
ReconPhys: Reconstruct Appearance and Physical Attributes from Single Video
ViVa: A Video-Generative Value Model for Robot Reinforcement Learning
Jeff-Wang
submitted a
paper to Daily Papers 8 days ago
Jeff-Wang
submitted a
paper to Daily Papers 11 days ago
SteveZeyuZhang
submitted a
paper to Daily Papers about 1 month ago
Jeff-Wang
submitted a
paper to Daily Papers about 1 month ago
SteveZeyuZhang
authored a
paper about 2 months ago
SteveZeyuZhang
submitted a
paper to Daily Papers about 2 months ago
SteveZeyuZhang
authored 2
papers about 2 months ago
SteveZeyuZhang
submitted 4
papers to Daily Papers about 2 months ago
OCR-Agent: Agentic OCR with Capability and Memory Reflection
Paper • 2602.21053 • Published • 2
OmniOCR: Generalist OCR for Ethnic Minority Languages
Paper • 2602.21042 • Published • 2
StereoAdapter-2: Globally Structure-Consistent Underwater Stereo Depth Estimation
Paper • 2602.16915 • Published
MMA: Multimodal Memory Agent
Paper • 2602.16493 • Published • 9
SteveZeyuZhang
authored 8
papers about 2 months ago
MoRL: Reinforced Reasoning for Unified Motion Understanding and Generation
Paper • 2602.14534 • Published • 3
Light4D: Training-Free Extreme Viewpoint 4D Video Relighting
Paper • 2602.11769 • Published • 2
Code2Worlds: Empowering Coding LLMs for 4D World Generation
Paper • 2602.11757 • Published • 4
GeneralVLA: Generalizable Vision-Language-Action Models with Knowledge-Guided Trajectory Planning
Paper • 2602.04315 • Published • 1
V-Retrver: Evidence-Driven Agentic Reasoning for Universal Multimodal Retrieval
Paper • 2602.06034 • Published • 8
SafeMo: Linguistically Grounded Unlearning for Trustworthy Text-to-Motion Generation
Paper • 2601.00590 • Published
WebCryptoAgent: Agentic Crypto Trading with Web Informatics
Paper • 2601.04687 • Published
MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training
Paper • 2407.19546 • Published