MetaSymbO proposes a three-agent framework with symbolic latent evolution that improves structural validity and language alignment for metamaterial design from free-form text intents.
Large language model agent as a mechanical designer
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CFDLLMBench is a new benchmark suite with CFDQuery, CFDCodeBench, and FoamBench to evaluate LLMs on graduate-level CFD knowledge, numerical reasoning, and context-dependent code implementation.
A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.
citing papers explorer
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METASYMBO: Multi-Agent Language-Guided Metamaterial Discovery via Symbolic Latent Evolution
MetaSymbO proposes a three-agent framework with symbolic latent evolution that improves structural validity and language alignment for metamaterial design from free-form text intents.
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CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics
CFDLLMBench is a new benchmark suite with CFDQuery, CFDCodeBench, and FoamBench to evaluate LLMs on graduate-level CFD knowledge, numerical reasoning, and context-dependent code implementation.
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Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges
A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.