Settle: Learning When to Stop Reasoning
Settle extends the accuracy-token-count Pareto frontier of the evaluated stopping methods and predicts whether a correct answer will remain correct in completed traces.
We have 3 of 6 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Settle extends the accuracy-token-count Pareto frontier of the evaluated stopping methods and predicts whether a correct answer will remain correct in completed traces.
Adaptive Calibration is introduced, a novel calibration strategy for facial recognition that maps cosine similarity between normalized embeddings to well-calibrated probabilities and provides a practical solution for equitable facial recognition without requiring demographic group annotations.
It is found that safety outcomes are highly sensitive to both the choice of fine-tuning language and the evaluation language, with adversarial compliance rates increasing four-fold in some settings.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.