Surprisal minimization over goal-directed alternatives generated by language models provides the strongest account of production choices in open-ended dialogue compared to uniform information density or length-based costs.
Journal of pharmacokinetics and biopharmaceutics , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A pre-registered protocol rejects tail-shape claims in standard LLM toxicity evaluation as false positives under two different scorer families.
citing papers explorer
-
Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialogue
Surprisal minimization over goal-directed alternatives generated by language models provides the strongest account of production choices in open-ended dialogue compared to uniform information density or length-based costs.
-
Tail-Shape Estimation in LLM Evaluation Is Fragile: A Protocol for Diagnosing False Positives
A pre-registered protocol rejects tail-shape claims in standard LLM toxicity evaluation as false positives under two different scorer families.