collaborators

5 papers

cs.AI2026

GRACE: LLM-Grounded Semantic Metric Spaces for Scalable Mixed-Data Clustering

Zihua Yang, Zhencheng Xie, Junyang Chen +4

Clustering mixed tabular data requires a unified metric space to bridge the inherent heterogeneity between continuous numerical measurements and discrete categorical symbols. Tradi…

cs.LG2026

Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models

Zihua Yang, Xin Liao, Yiqun Zhang +1

Qualitative data are widespread in domains such as healthcare, marketing, and bioinformatics, where clustering offers a fundamental tool for pattern discovery. A core difficulty of…

hep-ph2026

Two-loop Six-point Planar Massless Feynman Integrals to Higher Orders

Yuanche Liu, Antonela Matijašić, Tiziano Peraro +3

In this work, we calculate two-loop six-point planar massless Feynman integrals at higher orders in the dimensional regulator , corresponding to higher transcendental weights.…

cs.LG2026

One-Shot Federated Clustering of Non-Independent Completely Distributed Data

Yiqun Zhang, Shenghong Cai, Zihua Yang +3

Federated Learning (FL) that extracts data knowledge while protecting the privacy of multiple clients has achieved remarkable results in distributed privacy-preserving IoT systems,…

cs.LG2026

Stitch the Fragments: One-Shot Hierarchical Federated Clustering

Shenghong Cai, Zihua Yang, Yang Lu +4

Federated Clustering (FC) faces a critical bottleneck in real-world scenarios, i.e., global clusters are rarely intact, often fragmenting into incomplete, multi-granular unlabeled…