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Researcher

Song Peiyang

Researcher at Stanford University

An undergraduate student in Computer Science at the California Institute of Technology who conducts research.

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Stanford researchers propose a taxonomy explaining LLM reasoning gaps despite strong benchmark performance
Stanford UniversityresearchneutralFeb 10, 2026

Stanford researchers introduce a comprehensive taxonomy framework categorizing LLM reasoning failures into embodied/non-embodied types and fundamental, application-specific, and robustness failure classes to systematically understand persistent reasoning gaps.

“Co-author of Stanford paper on Large Language Model Reasoning Failures survey.”

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