CoWorld Reasoner: Agentic Multimodal Reasoning with the Evolving Video World Model-Driven Harness
To support flexible visual imagination for diverse reasoning tasks, we introduce CoWorld Reasoner, an agentic framework that uses a VWM as a unified visual reasoning engine.
ProofPaper ↗
Key points
- As Vision-Language Models (VLMs) advance, they are increasingly expected to perform spatiotemporal reasoning over motion, actions, and view changes beyond what the input images show.
- Video World Models (VWMs) provide a natural unified engine for visual imagination by generating task-relevant visual content as additional evidence.
- We further introduce VLM-VWM Harness Co-Evolution, which jointly revises tools, skills, and execution code based on execution feedback while keeping both model weights fixed.
- Across seven benchmarks spanning spatial intelligence, temporal and causal reasoning, and perceptual reasoning, CoWorld Reasoner outperforms direct reasoning with the same VLM.
Sources (2)
- [1]CoWorld Reasoner: Agentic Multimodal Reasoning with the Evolving Video World Model-Driven HarnessarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 15, 01:59 PM
To support flexible visual imagination for diverse reasoning tasks, we introduce CoWorld Reasoner, an agentic framework that uses a VWM as a unified visual reasoning engine.
As Vision-Language Models (VLMs) advance, they are increasingly expected to perform spatiotemporal reasoning over motion, actions, and view changes beyond what the input images show.
- [2]CoWorld Reasoner: Agentic Multimodal Reasoning with the Evolving Video World Model-Driven HarnessHugging Face Daily Papers · Oct 15, 12:00 AM · same content
Extractive summary: sentences quoted from the sources.
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