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22 papers · 1 filter

cs.LG2026

Large Language Bayes Is Not Reparameterisation-Invariant

Jian Xu

Large Language Bayes (LLB) answers an informal modelling question by sampling candidate probabilistic programs from a language model, running approximate inference on each, and ave…

cs.LG2026

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

Jian Xu, Delu Zeng, John Paisley

Joint audio--video (AV) generators are trained on data in which \emph{what an event looks like} and \emph{what it sounds like} are spuriously correlated. We present a \emph{control…

cs.LG2026

Mode Collapse Is Cheap to Detect: A Ground-Truth-Free Pre-Flight Check for Neural Samplers

Jian Xu

Neural samplers are trained against an unnormalised target with no samples from , which leaves the practitioner with no way to tell whether an expensive trainin…

cs.LG2026

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

Jian Xu, Delu Zeng, John Paisley +1

A large graph is often available only in part: a crawl stopped by its budget, a panel, a partial dump. When the sampled fraction is known by design the total edge count follows…

cs.LG2026

Evaluating Generative Time-Series Models on Data with Point Masses

Jian Xu

Many of the series that generative time-series models are benchmarked on place a large probability mass on a single value --- it does not rain, no ride is requested, no part is ord…

cs.CV2026

Diagnosing Under-Development of Irreversible Processes in Video Generation

Jian Xu, Yanning Wu, Delu Zeng +2

Many physical attributes are \emph{irreversible}: ice melts but does not re-freeze, paper chars but does not un-burn. Do video generators respect this? We show the question is hard…

cs.CV2026

Look Again Before You Abstain:Budgeted Conformal Evidence Acquisition for Reliable Vision-Language Model

Jian Xu, Yanning Wu, Delu Zeng +2

Large vision-language models (LVLMs) hallucinate: they assert visual details that the image does not support. A principled remedy is selective prediction with a distribution-free g…

cs.LG2026

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

Jian Xu, Delu Zeng, John Paisley +1

Large language models (LLMs) are increasingly used as cheap, scalable judges that compare candidate outputs pairwise. Because such judges prefer verbose or well-formatted answers,…

quant-ph2026

Fixed-Protocol Amortized MPS Tomography with Conformalized Predictive Uncertainty

Jian Xu, Delu Zeng, John Paisley +1

Quantum state tomography is sample-starved, and the states one prepares live on a narrow, learnable manifold. A prior-only control shows that on concentrated families a pri…

quant-ph2026

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

Jian Xu, Delu Zeng, John Paisley +1

Parameterized quantum circuits (PQCs) are increasingly used as policies and value functions in quantum reinforcement learning, yet it remains unclear when and why quantum policies…

cs.LG2026

Active Quantum Kernel Acquisition for Gaussian Process Regression

Jian Xu, Artur Miroszewski, John Paisley +2

Quantum kernel estimation on near-term hardware is shot-budgeted: every entry of the kernel Gram matrix is a Bernoulli expectation that must be sampled with a finite number of circ…

cs.LG2026

Calibration, Not Compilation: Detecting and Repairing Misspecified Probabilistic Programs Written by Language Models

Jian Xu, Delu Zeng, John Paisley +1

Language models increasingly write probabilistic programs (in NumPyro, Stan, or Pyro), but a program that compiles, runs, and passes every unit test can still be \emph{statisticall…

cs.CV2026

What Do Flow-Based Inverse Solvers Approximate? A Posterior-Transport View

Jian Xu, Delu Zeng, John Paisley +1

A growing family of training-free solvers -- FlowDPS, FLOWER, PnP-Flow and their diffusion ancestors (DPS, DAPS) -- repurpose a pretrained flow-matching prior to solve imaging inve…

cs.LG2026

Intrinsic Flow Matching on Quantum Pure-State Manifolds with Phase-Aligned Transport

Jian Xu, Delu Zeng, John Paisley +1

Quantum pure-state ensembles live on complex projective space, making flat Euclidean generative modeling geometrically mismatched. We introduce Intrinsic Flow Matching (IFM), a det…

cs.LG2026

Effective Dimension Governs Generalization in Quantum Kernel Vision Models

Jian Xu, Delu Zeng, John Paisley +1

Recent quantum vision models-quantum vision transformers and quantum convolutional networks-report two striking but unexplained empirical phenomena: (i) ansatze with more, or more…

quant-ph2026

Higher-Order Token Interactions via Quantum Attention

Jian Xu, Chao Li, Delu Zeng +2

Standard dot-product self-attention computes, in a single layer, only pairwise (order-2) interactions between tokens; representing a generic order- interaction is known to requi…

cs.LG2026

Implicit Variational Rejection Sampling

Jian Xu, Shigui Li, Wei Chen +6

Variational Inference (VI) is a fundamental inference technique in Bayesian machine learning for approximating complex posterior distributions. Traditional VI often relies on the m…

cs.LG2026

The Right Measure for Physics-Constrained Generation: A Co-Area Correction for Posterior-Consistent PDE Inverse Problems

Jian Xu, Yanning Wu, Delu Zeng +2

Generative models -- diffusion and flow matching -- are increasingly used to solve partial differential equation (PDE) inverse problems, enforcing the governing physics as a \emph{…

cs.LG2026

Spectral Anatomy of Quantum Gaussian Process Kernels

Jian Xu, Chao Li, Guang Lin +4

Two recent results have reshaped quantum Gaussian processes (QGPs). On the one hand, \citet{lowe2025assessing} rule out the exponential speedups claimed by HHL-based QGP regression…

cs.LG2026

On the Approximation Complexity of Matrix Product Operator (MPO) Born Machines

Chao Li, Zerui Tao, Yuchen Cong +2

Matrix product operator Born machines (MPO-BMs) are tractable tensor-network models for probabilistic modeling, yet their approximation capabilities remain poorly understood in the…

cs.LG2026

AQKA: Active Quantum Kernel Acquisition Under a Shot Budget

Jian Xu, Chao Li, Delu Zeng +2

Estimating an quantum kernel from circuit fidelities requires measurement shots, the dominant bottleneck for deployment on near-term hardware. Existing budg…

stat.ML2026

Local-Time Riemannian Score Matching on the Quantum Pure-State Manifold

Jian Xu, Wei Chen, Shigui Li +4

Score-based diffusion can be defined intrinsically on the manifold of quantum pure states, with the Fubini--Study metric, but no closed-form transition density…