2 citations · 2 across the 32 of their papers we have counts for
20 papers · 1 filter
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…