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Research questionHow can LLMs reason reliably about physical systems from large, fine-grained simulator traces?Simulator traces contain extensive numerical and semantic state data, making them difficult for LLMs to interpret efficiently and validate reliably. The challenge is to preserve information needed for reasoning without overwhelming the model with fine-grained details.
AI
Code Generation & Program Synthesis
Reasoning
Latest papersRecent research connected to this question, newest first.Discovering High Level Patterns from Simulation TracesApplies to LLMs that use physical simulators and their traces as context. The source reports evidence from a physics benchmark and an example in which natural-language goals are converted into reward programs; it also describes optional expert-provided pattern labels and transparent synthesized detectors.research paper · Sep 3, 2026
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