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Statist.] 10.1214/aos/1176344136 , 6, 461

Tool reference. 83% of classified Pith citations use this work as a method, library, or software dependency, not as a substantive claim.

55 Pith papers citing it
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Fast Computation of Free-Support Wasserstein Medians

stat.CO · 2026-06-17 · unverdicted · novelty 7.0

Direct fixed-weight solver for free-support Wasserstein medians relocates atoms using OT barycentric projections and inverse-distance weights, achieving monotone descent on smoothed objectives with fewer subproblems than nested Weiszfeld baselines.

The Regularizing Power of Language-Training Deepfake Detectors

cs.CV · 2026-05-29 · unverdicted · novelty 7.0

A dual-encoder deepfake detector pairs a frozen specialist with a LoRA-tuned MLLM, trained first via binary alignment then via RL to reward explain-then-classify behavior, yielding improved cross-dataset performance and interpretability.

ProactBench: Beyond What The User Asked For

cs.LG · 2026-05-09 · unverdicted · novelty 7.0

ProactBench measures LLM conversational proactivity in three phases using 198 multi-agent dialogues and finds recovery behavior hard to predict from existing benchmarks.

Two-Sample Homogeneity Test via Entropic Optimal Transport

stat.ME · 2026-06-09 · unverdicted · novelty 6.0

Proposes and analyzes a homogeneity test using squared L2 distance of empirical EOT maps to uniform-on-ball reference, with FCLT, Gaussian quadratic null limit, consistency, local power, and weighted multiplier bootstrap.

Absorbing Many-Body Correlations into Core-Optimized Orbitals

quant-ph · 2026-05-21 · unverdicted · novelty 6.0

COO co-optimizes orbitals with TrimCI to absorb many-body correlations into the basis, cutting determinant count by orders of magnitude for iron-sulfur clusters versus localized bases or DMRG.

Bayesian Modeling and Prediction of Generalized Contact Matrices

stat.ME · 2026-05-07 · unverdicted · novelty 6.0

A Bayesian model for multi-feature contact matrices that uses tensor structures and contingency table theory to satisfy structural constraints and impute missing contact features, validated on simulations and US/German survey data.

A Semi-Supervised Kernel Two-Sample Test

stat.ML · 2026-05-03 · unverdicted · novelty 6.0

A semi-supervised kernel two-sample test integrates unlabeled covariate data to achieve asymptotic normality under the null, higher power than standard kernel tests, and consistency against fixed and local alternatives.

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