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John W. Paisley

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Consist-Retinex: One-Step Noise-Emphasized Consistency Training Accelerates High-Quality Retinex Enhancement

Consist-Retinex is proposed, which first uses a Retinex Transformer Decomposition Network to obtain paired reflectance and illumination maps, then trains two conditional consistency models with a Retinex-aware dual objective and adaptive noise-emphasized fixed-point sampling.

Jian Xu, Wei Chen, Shigui Li et al. · 0 citations

Neural Bridge Processes

The results suggest that bridge-anchored generative paths provide a general mechanism for strengthening conditional stochastic function modeling.

Jian Xu, Yican Liu, Qi-Bin Zhao et al. · 0 citations
#machine learning Preprint Aug 2026

Partially Observed Sparse Graphs: The Unknown Sampling Rate is a Tail Index

A large graph is often available only in part: a crawl stopped by its budget, a panel, a partial dump. When the sampled fraction $s$ is known by design the total edge count follows from $\hat e=e_s/s^2$ and no model is needed. We treat the case where $s$ is unknown and the population size is known. Our main result is a...

Jian Xu, Delu Zeng, John W. Paisley et al. · 0 citations
#machine learning Preprint Aug 2026

Intervention, Not Shared Latents: Blocking Visual Shortcuts in Audio-Video Generation

It is proved that counterfactual invariance is necessary and sufficient to identify the causal predictor, and the mechanism from feature-vector SCMs to procedural pixel video, real images with spectrogram audio, moving real digits, and a conditional generator is verified.

Jian Xu, Delu Zeng, John W. Paisley · 0 citations
Preprint Jul 2026

Entanglement as a Structural Complexity Axis: A PAC-Bayesian View of Generalization in Quantum Policies and Value Functions

A PAC-Bayesian account in which quantum policy design is reframe around an entanglement--generalization trade-off rather than expressivity alone is given, where entangled circuits consistently generalize worse than non-entangled circuits of equal parameter count.

Jian Xu, Delu Zeng, John W. Paisley et al. · 0 citations
Preprint Jul 2026

When Can You Debias an LLM Judge? Identifiability Limits, a Test, and Designs for Top-k Ranking

The contribution is accordingly not a better estimator but a characterization of \emph{when prior-based correction is justified}, plus designs that supply the missing information when it is not, plus designs that supply the missing information when it is not.

Jian Xu, Delu Zeng, John W. Paisley et al. · 0 citations

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