activity
20242026
most citedWatermarking Continuous Tabular Data Generation

1 citations · 1 across the 10 of their papers we have counts for

collaborators

13 papers

math.PR2026

The Berry-Esseen Constant Conjecture is Eventually True

Hengzhi He, Guang Cheng

We prove that the Esseen's constant is valid in the iid Berry--Esseen inequality as long as the sample sizes . The threshold is universal over all real summ…

math.CO2026

Fractional Triangle Decompositions at Partite Minimum Degree

Hengzhi He, Guang Cheng

We prove that every triangle-divisible balanced tripartite graph whose vertex classes have size and whose partite minimum degree is at least admits a fractional triangle…

math.ST2026

Tensor-normal maximum likelihood estimation at the operator-norm sample threshold

Hengzhi He, Guang Cheng

Let be independent Gaussian tensors in with a common covariance matrix given by the Kronecker product of …

math.ST2026

Asymptotically Lossless Exact and Pivotal E-Values

Hengzhi He, Guang Cheng

Consider testing a finite composite null $\cP={P_1,\ldots,P_L}$ against a simple alternative using i.i.d. observations. Let denote the supremum of the expected log…

math.ST2026

Sharp proper estimation of fixed-component Gaussian location mixtures in polynomial time

Hengzhi He, Guang Cheng

We consider a mixture of at most unit-covariance Gaussians in whose means belong to a fixed-radius ball, with no separation or minimum-weight condition. Doss, Wu…

cs.LG2026

Let the Target Select for Itself: Data Selection via Target-Aligned Paths

Huitao Yang, Hengzhi He, Guang Cheng +1

Targeted data selection seeks training examples from a candidate pool that improve downstream task performance. While trajectory-based selectors effectively guide this process, exi…

cs.CR2026

Authenticated Contradictions from Desynchronized Provenance and Watermarking

Alexander Nemecek, Hengzhi He, Guang Cheng +1

Cryptographic provenance standards such as C2PA and invisible watermarking are positioned as complementary defenses for content authentication, yet the two verification layers are…

stat.ME2025

Optimal Watermark Generation under Type I and Type II Errors

Hengzhi He, Shirong Xu, Alexander Nemecek +3

Watermarking has recently emerged as a crucial tool for protecting the intellectual property of generative models and for distinguishing AI-generated content from human-generated d…

stat.ML2025

A Probabilistic Perspective on Model Collapse

Shirong Xu, Hengzhi He, Guang Cheng

In recent years, model collapse has become a critical issue in language model training, making it essential to understand the underlying mechanisms driving this phenomenon. In this…

stat.ML2025

Recursive Learning Without Collapse: A Weighting-Based Stabilization Framework

Hengzhi He, Shirong Xu, Guang Cheng

Recent studies identified an intriguing phenomenon in recursive generative model training known as model collapse, where models trained on data generated by previous models exhibit…

cs.CR2024

Watermarking Generative Categorical Data

Bochao Gu, Hengzhi He, Guang Cheng

In this paper, we propose a novel statistical framework for watermarking generative categorical data. Our method systematically embeds pre-agreed secret signals by splitting the da…

cs.CR2024★ 1 cited

Watermarking Continuous Tabular Data Generation

Hengzhi He, Peiyu Yu, Junpeng Ren +2

In this paper, we introduce a simple yet effective tabular data watermarking mechanism with statistical guarantees. We show theoretically that the proposed watermark can be effecti…

cs.LG2024

"Noisier" Noise Contrastive Eestimation is (Almost) Maximum Likelihood

Peiyu Yu, Dinghuai Zhang, Hengzhi He +10

Noise Contrastive Estimation (NCE) has fueled major breakthroughs in representation learning and generative modeling. Yet a long-standing challenge remains: accurately estimating r…