Fang Kai — accepted AI-conference papers

2026

PointCHR: Point Cloud Analysis via Curvature-Aware Hyperbolic Rectification

Xinxing Yu, Liying Yang, Hao Mo, Hui Ma, Fang Kai, Ajian Liu +1

ICML 2026poster

High-curvature regions in 3D point clouds encapsulate critical fine-grained geometric semantics yet exhibit a distinct long-tail sparsity in their spatial distribution. The inherent limitations of polynomial volume growth in Euclidean space frequently render these intricate geometric features challe…

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2026

Revisiting Contrastive Learning in Collaborative Filtering via Parallel Graph Filters

Fang Kai, Yu Zhang, Kaibin Wang, Lei Sang, Yiwen Zhang

AAAI 2026technical

Graph Contrastive Learning (GCL) has recently emerged as a powerful paradigm for modeling user–item interactions and learning high-quality representations in recommender systems. While existing GCL-based methods benefit from data augmentation and sampling strategies, they often overlook the inherent

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