UniVR: Thinking in Visual Space for Unified Visual Reasoning
- Published
- Source
- arXiv
- Paper number
- 629
- Field
- Computer Vision
- arXiv ID
- 2607.12800
Key points
- VR-GRPO combines overall outcome rewards with rewards for error-prone steps to learn logical and physical consistency in visual reasoning.
- It built the VR-X benchmark from 16 sources, bringing long-horizon manipulation, spatial puzzles, and physical reasoning together in a purely visual format.
- UniVR improved by up to 25% on VR-X, and stronger visual reasoning also improved performance on multiple multimodal-understanding benchmarks.
- It released code, data, and models for research on planning and reasoning in visual space without textual explanations.
- The 34B model and long-video training require substantial computational resources, and step rewards also depend on a general-purpose VLM that lacks detailed physical knowledge.
Paper links
External research summaries. These are not HDATF publications or measured product results.