1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2025★ 1 cited
SHAP Distance: An Explainability-Aware Metric for Evaluating the Semantic Fidelity of Synthetic Tabular Data
Ke Yu, Shigeru Ishikura, Yukari Usukura +2
Synthetic tabular data, which are widely used in domains such as healthcare, enterprise operations, and customer analytics, are increasingly evaluated to ensure that they preserve…
cs.LG2025
GraphFedMIG: Tackling Class Imbalance in Federated Graph Learning via Mutual Information-Guided Generation
Xinrui Li, Qilin Fan, Tianfu Wang +3
Federated graph learning (FGL) enables multiple clients to collaboratively train powerful graph neural networks without sharing their private, decentralized graph data. Inherited f…
cs.CL2025
Rethinking Text-based Protein Understanding: Retrieval or LLM?
Juntong Wu, Zijing Liu, He Cao +6
In recent years, protein-text models have gained significant attention for their potential in protein generation and understanding. Current approaches focus on integrating protein-…