chain-of-thought prompting 1information density 1large language models 1post-hoc compression 1reasoning efficiency 1
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cs.AI2026
Valid Necessary: Diagnosing Latent Inefficiency in Chain-of-Thought
Daeyeop Lee, Hwanjo Yu
The paper identifies and diagnoses inefficient reasoning steps in chain-of-thought prompting for large language models, introducing a benchmark and a training-free metric (CAID) to…
cs.AI2026
COMPASS: A Framework for Evaluating Organization-Specific Policy Alignment in LLMs
Dasol Choi, DongGeon Lee, Brigitta Jesica Kartono +6
As large language models are deployed in high-stakes enterprise applications, from healthcare to finance, ensuring adherence to organization-specific policies has become essential.…