惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Google DeepMind News
Google DeepMind News
罗磊的独立博客
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Last Week in AI
Last Week in AI
云风的 BLOG
云风的 BLOG
T
The Blog of Author Tim Ferriss
Y
Y Combinator Blog
A
About on SuperTechFans
WordPress大学
WordPress大学
B
Blog
Martin Fowler
Martin Fowler
Jina AI
Jina AI
I
InfoQ
P
Proofpoint News Feed
小众软件
小众软件
S
SegmentFault 最新的问题
V
V2EX
B
Blog RSS Feed
量子位
大猫的无限游戏
大猫的无限游戏
aimingoo的专栏
aimingoo的专栏
博客园 - 三生石上(FineUI控件)
MongoDB | Blog
MongoDB | Blog
美团技术团队

math updates on arXiv.org

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization Non-normal spectral signatures of instability in neural network training dynamics Optimization of randomized neural networks for transfer operator approximation Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy Training-Free Looped Transformers Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries Asymmetric Scaling Laws from Sparse Features Is Dimensionality a Barrier for Retrieval Models? RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs Commutator-Induced Uncertainty in VAEs Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating Instance-Optimal Estimation with Multiple LLM Judges on a Budget Entropy Equivalence Testing Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation Any-Dimensional Invariant Universality Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models Anytime Training with Schedule-Free Spectral Optimization Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology The General Theory of Localization Methods Group-Algebraic Tensors: Provably-optimal Equivariant Learning and Physical Symmetry Discovery General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Proximal basin hopping: global optimization with guarantees
A disproof of the uniform witness conjecture
[Submitted on 23 Jun 2026] · 2026-06-24 · via math updates on arXiv.org

View PDF HTML (experimental)

Abstract:The study of $(d+1)$-uniform set systems with VC-dimension at most $d$ links the Erdős--Ko--Rado theorem with VC-dimension. But already in 1997, Ahlswede and Khachatrian showed that this is not the right extension of the Erdős--Ko--Rado theorem. In 2025, Chao, Xu, Yip and Zhang proposed the uniform witness conjecture as a possible right extension: for $0\le s\le d$, if every set of a $(d+1)$-uniform family has a missing trace of the same fixed size $s$, then the family should have size at most $\binom{n-1}{d}$. They proved the conjecture when $s=d$, and when $s=1$ and $n$ is large. Very recently, Chao, Xu and Zakharov proved the conjecture when $s\le \frac{d}{2}$ and $n$ is large.
We fill in the missing half of the picture, although the picture is not the one suggested by the conjecture. More precisely, for $d\ge 4$ and $\left\lceil \frac{d+2}{2}\right\rceil\le s\le d-1$, we construct such a family $\mathcal{F}\subseteq\binom{[n]}{d+1}$ with $|\mathcal{F}|=\binom{n-1}{d}+\binom{n-2(d+1-s)-2}{2s-d-2}$ for every $n\ge2(d+1)$, thereby disproving the uniform witness conjecture.

Submission history

From: Zixiang Xu [view email]
[v1] Tue, 23 Jun 2026 16:35:12 UTC (8 KB)