Author

Phil Blandfort

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#artificial intelligence Preprint Oct 2026

An Investigation of Model Coherence: Narrow Finetunes Contradict Themselves Under Resampling

A large body of research measures model coherence based on output variance without adequately considering competing causes. We identify two such causes, ambiguity and indifference, and we introduce a set of 175 questions where contradicting answers cannot easily be explained by either. We then measure incoherence in te...

Robert Graham, Yariv Barsheshat, Phil Blandfort et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Strangers to Themselves: What Language Models Say About Themselves Is Generic

Language models can fluently describe how they would behave: whether they would cave to pushback, misuse a tool, or lie under pressure. Is that description actually about the model speaking? We turn self-knowledge into a prediction test. Across nine behavioral evaluations, we measure how a model behaves under different...

Phil Blandfort, Urja Pawar · 0 citations