57 citations · 217 across the 32 of their papers we have counts for
32 papers
SkillTFM: Gated Skill Evolution for Training-Free Adaptation of Tabular Foundation Models
Yi He, Zhengkang Guan, Anpeng Wu +3
Tabular data are ubiquitous in real-world applications and are crucial for data-driven prediction and decision-making across science, industry, finance, healthcare, and public serv…
FedCFA: Alleviating Simpson's Paradox in Model Aggregation with Counterfactual Federated Learning
Zhonghua Jiang, Jimin Xu, Shengyu Zhang +5
Federated learning (FL) is a promising technology for data privacy and distributed optimization, but it suffers from data imbalance and heterogeneity among clients. Existing FL met…
Goal-Oriented Prompt Attack and Safety Evaluation for LLMs
Chengyuan Liu, Fubang Zhao, Lizhi Qing +4
Large Language Models (LLMs) presents significant priority in text understanding and generation. However, LLMs suffer from the risk of generating harmful contents especially while…
MEDOE: A Multi-Expert Decoder and Output Ensemble Framework for Long-tailed Semantic Segmentation
Junao Shen, Long Chen, Kun Kuang +3
Long-tailed distribution of semantic categories, which has been often ignored in conventional methods, causes unsatisfactory performance in semantic segmentation on tail categories…
Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series
Anpeng Wu, Haoxuan Li, Kun Kuang +2
Learning directed acyclic graphs (DAGs) to identify causal relations underlying observational data is crucial but also poses significant challenges. Recently, topology-based method…
Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization
Yunze Tong, Junkun Yuan, Min Zhang +4
Domain generalization (DG) is a prevalent problem in real-world applications, which aims to train well-generalized models for unseen target domains by utilizing several source doma…