LLMs exhibit myopic planning in games, with move choices driven by shallow nodes despite deep reasoning traces, in contrast to human deep-search reliance.
Byrd, Peihuang Lu, Jorge Nocedal, and Ciyou Zhu
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
A majorization-minimization framework turns IRT into scalable matrix factorization subproblems for LLM evaluation, delivering orders-of-magnitude speedups with identifiability guarantees.
citing papers explorer
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Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning
LLMs exhibit myopic planning in games, with move choices driven by shallow nodes despite deep reasoning traces, in contrast to human deep-search reliance.
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An Interpretable and Scalable Framework for Evaluating Large Language Models
A majorization-minimization framework turns IRT into scalable matrix factorization subproblems for LLM evaluation, delivering orders-of-magnitude speedups with identifiability guarantees.