Open-o3-Video-v2: Seek, Ground, and Reason with Verifiable Spatio-Temporal Evidence
We introduce Open-o3-Video-v2, which formulates video reasoning as a unified agentic evidencegrounded process.
ProofPaper ↗
Key points
- Reliable video reasoning requires models to produce correct answers and expose supporting visual evidence.
- Open-o3-Video enables verifiable reasoning by embedding timestamps and object-level bounding boxes into reasoning traces, but is restricted to frames from an initial sparse sampler.
- To support this behavior, we construct STGR-v2-CoT135K, including 52K multi-turn agentic grounded reasoning trajectories, and STGR-v2-RL-13K for reinforcement learning.
- These results show that active evidence acquisition and verifiable object-level grounding are complementary for reliable video reasoning.
Sources (2)
- [1]Open-o3-Video-v2: Seek, Ground, and Reason with Verifiable Spatio-Temporal EvidenceHugging Face Daily Papers · Oct 13, 12:00 AM
We introduce Open-o3-Video-v2, which formulates video reasoning as a unified agentic evidencegrounded process.
Reliable video reasoning requires models to produce correct answers and expose supporting visual evidence.
- [2]Open-o3-Video-v2: Seek, Ground, and Reason with Verifiable Spatio-Temporal EvidencearXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 13, 03:36 AM · same content
Extractive summary: sentences quoted from the sources.
Before this
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