AI Research
PhysMent: An Interactive Approach For LLM Reasoning In Physics Problems
Bridging the gap between static knowledge and active physical reasoning through interactive experimentation.
Large language models (LLMs) perform strongly on static science benchmarks, yet their ability to reason about the physical world through active experimentation remains poorly understood. We introduce PhysMent, a benchmark that evaluates LLM physical reasoning via iterative, toolm...
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ArXiv CS.CL
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ArXiv CS.CL
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PhysMent shifts the focus of AI research from static knowledge retrieval to active experimentation and iterative reasoning. This benchmark highlights the critical need for LLMs to simulate physical outcomes and correct their logic through environmental feedback.
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