2 citations · 2 across the 32 of their papers we have counts for
32 papers
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…
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…
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…
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…
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,…
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…
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…
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…
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…
Onsager-Machlup Posterior Transport for Deep Gaussian Processes
Jian Xu, Delu Zeng, John Paisley +1
Approximate inference over inducing variables is the central computational bottleneck of Deep Gaussian Processes (DGPs). Existing methods either fit an explicit density $q_ϕ(\bU)$…
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…
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…
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…
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…
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{…
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…
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…
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…
Towards Disentangled Preference Optimization Dynamics: Suppress the Loser, Preserve the Winner
Wei Chen, Yubing Wu, Junmei Yang +5
Preference optimization is widely used to align large language models (LLMs) with human preferences. However, many margin-based methods also suppress the chosen response when they…
A Minimum Variance Path Principle for Accurate and Stable Score-Based Density Ratio Estimation
Wei Chen, Jiacheng Li, Shigui Li +4
Score-based methods are powerful across machine learning, but they face a paradox: theoretically path-independent, yet practically path-dependent. We resolve this by proving that p…
Consist-Retinex: One-Step Noise-Emphasized Consistency Training Accelerates High-Quality Retinex Enhancement
Jian Xu, Wei Chen, Shigui Li +3
Retinex-based low-light image enhancement benefits from separating reflectance and illumination, yet recent generative approaches often rely on iterative sampling and are difficult…
Diffusion Bridge Variational Inference for Deep Gaussian Processes
Jian Xu, Qibin Zhao, John Paisley +1
Deep Gaussian processes (DGPs) enable expressive hierarchical Bayesian modeling but pose substantial challenges for posterior inference, especially over inducing variables. Denoisi…
Diffusion Secant Alignment for Score-Based Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li +6
Estimating density ratios has become increasingly important with the recent rise of score-based and diffusion-inspired methods. However, current tangent-based approaches rely on a…
Neural Bridge Processes
Jian Xu, Yican Liu, Delu Zeng +2
Learning stochastic functions from partially observed context-target pairs requires models that are expressive, uncertainty-aware, and strongly conditioned on inputs. Neural Diffus…