Integrating Simulation and Chain-of-thought Reasoning in Multimodal-Language Models For Physical Reasoning
Multimodal language models often need to reason about the physical dynamics of the world in order to answer questions appropriately. Various methods have emerged for solving physical reasoning tasks, and in particular, two leading approaches are Chain-of-Thought reasoning and physics-grounded simulation. However, relatively little is known about which particular problems can be solved by each approach. Some tasks may benefit from computationally expensive generative video simulations, whereas others may be solved equally well (or even better) with language-based reasoning. Our work addresses this by systematically comparing simulation and language reasoning across a variety of multimodal ...
| Authors | YingQiao Wang, Eric Bigelow, Tomer Ullman et al. |
|---|---|
| Primary category | cs.AI |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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