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cs.CL2026
LLMs Encode Their Failures: Predicting Success from Pre-Generation Activations
William Lugoloobi, Thomas Foster, William Bankes +1
Running LLMs with extended reasoning on every problem is expensive, but determining which inputs actually require additional compute remains challenging. We investigate whether the…
cs.CL2025
LLMs Encode How Difficult Problems Are
William Lugoloobi, Chris Russell
Large language models exhibit a puzzling inconsistency: they solve complex problems yet frequently fail on seemingly simpler ones. We investigate whether LLMs internally encode pro…