Tag
This paper establishes a sharp Loewner envelope for coefficient covariance under volume-sampled least squares, using feature-only geometry to analyze tightness conditions.
ProxyGuard introduces a direct method for inferring the reliability of randomized data release mechanisms with shared targets, using bounded risks and sealed targets to control errors and improve evaluation power in research proxy datasets.
This paper proposes NxN E-valuation, an e-value-based hypothesis certification algorithm that uses a large training set to let samples serve as null hypotheses for one another, enabling conditional randomization tests to certify LLM-proposed hypotheses without bespoke statistical procedures.
This paper presents a statistically-lossless quantization method for large language models, aiming to reduce model size without information loss.
Proposes Partially Adjudicated Design-Based Supervised Learning (PA-DSL), a method that corrects noisy human labels using a small set of adjudicated cases to debias automated classifiers, achieving nominal coverage and reducing RMSE by 10-17% in experiments.
Proposes Triospect, a three-dimensional framework that enhances AI-generated text detection robustness against 17 types of attacks, achieving 22.3% AUROC improvement over baselines.