Safety
Ψ-0.6: Adaptive Streams of Thought in a Unified Vision-Language World Model [R]
Chain-of-thought transformed AI reasoning, but it is limited to words. What's the physical-world analogue? Introducing Ψ-0.6, one model that reasons in *streams of thought*: words, depth, motion, came
Chain-of-thought transformed AI reasoning, but it is limited to words. What's the physical-world analogue? Introducing Ψ-0.6, one model that reasons in streams of thought: words, depth, motion, camera pose, and imagined scenes. And it learns when to use which! Ψ-0.6 surpasses leading open-weight models on complex spatial reasoning (MindCube, zero-shot). On FlowBench, it outperforms other world models at predicting how objects move. Trained on simulated rooms, it transfers to real robot tabletops. One model as perceiver, VLM, world model, reasoner, and policy. RL learns which representation to reason through. Thread (with video): https://x.com/khai_loong_aw/status/2115099953433600011 Paper: https://arxiv.org/abs/2610.32177 Website: https://neuroailab.github.io/psi-website/blog/psi-0-6.html Code: https://github.com/neuroailab/psi-0.6 submitted by /u/FaeriaManic [link] [comments]
Related
- Evo-World: A Lightweight Vision-Language-Action Model with Future Motion Prediction via Optical-Flow Supervision
- EWAM: Emergent Depth-Wise Specialization in a Unified Embodied Model -- From Semantic Understanding through Visual Foresight to Action
- X-Mind: Efficient Visual Chain-of-Thought via Predictive World Model for End-to-End Driving
- DeepThinkVLA: Enhancing Reasoning Capability of Vision-Language-Action Models
- When Reasoning Helps Action: Monitoring and Steering Chain-of-Thought in Vision-Language-Action Policies
Source: r/MachineLearning | 2026-10-27