TRIAGE evaluates LLMs on prospective metacognitive control by requiring a single plan for task selection, sequencing, and token allocation under a calibrated budget, revealing substantial gaps in current models across math, science, code, and knowledge tasks.
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Empirical runs across 56 settings on a fixed 500-question set show non-monotonic downstream scores and preprocessing losses, leading to a call for multi-stage RAG evaluation.
citing papers explorer
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TRIAGE: Evaluating Prospective Metacognitive Control in LLMs under Resource Constraints
TRIAGE evaluates LLMs on prospective metacognitive control by requiring a single plan for task selection, sequencing, and token allocation under a calibrated budget, revealing substantial gaps in current models across math, science, code, and knowledge tasks.
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A Systems-Level Analysis of Sensitivity, Robustness, and Stability in Retrieval-Augmented Generation
Empirical runs across 56 settings on a fixed 500-question set show non-monotonic downstream scores and preprocessing losses, leading to a call for multi-stage RAG evaluation.