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Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.
An efficient neural screening approach rapidly identifies circuit modules governing distinct behavioral transitions in response to pathogen exposure.
Researchers at UCSD and Columbia University published “ChipBench: A Next-Step Benchmark for Evaluating LLM Performance in AI-Aided Chip Design.” Abstract “While Large Language Models (LLMs) show ...
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