Hugging Face Trending Papers
Aug 18

Preference Is Not Intervention: The Structure and Stability Boundaries of Reader-Specific Evidence Utility

The paper investigates whether reader-specific differences in retrieval‑augmented generation (RAG) reflect reusable structure or merely input‑local interactions. By fixing query, evidence, task, scoring, and intervention, the authors find that nine readers disagree on the effect sign in 33% of cases, with reader×query interactions explaining 29.8% of utility variance. They further decompose heterogeneity into evidence activity, ordinal preference, and conditional signed direction, discovering that ordinal reader geometry is stable across multiple settings while signed geometry is task‑bounded, yet stable ordinal similarity does not predict cross‑reader intervention transfer.

arXiv Machine Learning
Sep 23

Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing

The paper introduces a new estimand for conditional distributional treatment effects that captures how treatments influence the entire outcome distribution, including variance and tail risks, in a covariate-dependent manner. It presents a doubly robust estimator that is minimax optimal locally and uses it to construct a test for global homogeneity of conditional potential outcome distributions. The test accommodates discrepancies beyond the maximum mean discrepancy, guarantees valid type‑1 error, is consistent against fixed alternatives, and includes a computationally efficient, permutation‑free algorithm with exact closed‑form expressions for two natural discrepancies.

By Saksham Jain, Alex Luedtke