6 papers
Optimal Deterministic Multicalibration and Omniprediction
Georgy Noarov, Aaron Roth
A model is multicalibrated on a collection of group weights if it is calibrated -- i.e. unbiased even conditional on its prediction -- not just overall, but also after reweight…
Optimal Lower Bounds for Online Multicalibration
Natalie Collina, Jiuyao Lu, Georgy Noarov +1
We prove tight lower bounds for online multicalibration, establishing an information-theoretic separation from marginal calibration. In the general setting where group functions ca…
The Sample Complexity of Multicalibration
Natalie Collina, Jiuyao Lu, Georgy Noarov +1
We study the minimax sample complexity of multicalibration in the batch setting. A learner observes i.i.d. samples from an unknown distribution and must output a (possibly rand…
Foundations of Top- Decoding For Language Models
Georgy Noarov, Soham Mallick, Tao Wang +5
Top- decoding is a widely used method for sampling from LLMs: at each token, only the largest next-token-probabilities are kept, and the next token is sampled after re-norma…
Statistical Early Stopping for Reasoning Models
Yangxinyu Xie, Tao Wang, Soham Mallick +6
While LLMs have seen substantial improvement in reasoning capabilities, they also sometimes overthink, generating unnecessary reasoning steps, particularly under uncertainty, given…
Stronger Neyman Regret Guarantees for Adaptive Experimental Design
Georgy Noarov, Riccardo Fogliato, Martin Bertran +1
We study the design of adaptive, sequential experiments for unbiased average treatment effect (ATE) estimation in the design-based potential outcomes setting. Our goal is to develo…