1 citations · 2 across the 10 of their papers we have counts for
11 papers
Efficient and Effective Table-Centric Table Union Search in Data Lakes
Yongkang Sun, Zhihao Ding, Huiqiang Wang +2
In data lakes, information on the same subject is often fragmented across multiple tables. Table union search aims to find the top-k tables that can be unioned with a query table t…
FlexGuard: Continuous Risk Scoring for Strictness-Adaptive LLM Content Moderation
Zhihao Ding, Jinming Li, Ze Lu +1
Ensuring the safety of LLM-generated content is essential for real-world deployment. Most existing guardrail models formulate moderation as a fixed binary classification task, impl…
Retrieve-and-Verify: A Table Context Selection Framework for Accurate Column Annotations
Zhihao Ding, Yongkang Sun, Jieming Shi
Tables are a prevalent format for structured data, yet their metadata, such as semantic types and column relationships, is often incomplete or ambiguous. Column annotation tasks, i…
Efficient Integration of Multi-View Attributed Graphs for Clustering and Embedding
Yiran Li, Gongyao Guo, Jieming Shi +2
A multi-view attributed graph (MVAG) G captures the diverse relationships and properties of real-world entities through multiple graph views and attribute views. Effectively utiliz…
Effective and Efficient Attributed Hypergraph Embedding on Nodes and Hyperedges
Yiran Li, Gongyao Guo, Chen Feng +1
An attributed hypergraph comprises nodes with attributes and hyperedges that connect varying numbers of nodes. Attributed hypergraph node and hyperedge embedding (AHNEE) maps nodes…
SteerConf: Steering LLMs for Confidence Elicitation
Ziang Zhou, Tianyuan Jin, Jieming Shi +1
Large Language Models (LLMs) exhibit impressive performance across diverse domains but often suffer from overconfidence, limiting their reliability in critical applications. We pro…
Enhancing Model Defense Against Jailbreaks with Proactive Safety Reasoning
Xianglin Yang, Gelei Deng, Jieming Shi +2
Large language models (LLMs) are vital for a wide range of applications yet remain susceptible to jailbreak threats, which could lead to the generation of inappropriate responses.…
RingFormer: A Ring-Enhanced Graph Transformer for Organic Solar Cell Property Prediction
Zhihao Ding, Ting Zhang, Yiran Li +2
Organic Solar Cells (OSCs) are a promising technology for sustainable energy production. However, the identification of molecules with desired OSC properties typically involves lab…
TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation
Ziang Zhou, Zhihao Ding, Jieming Shi +2
Graph Neural Networks (GNNs) are pivotal in graph-based learning, particularly excelling in node classification. However, their scalability is hindered by the need for multi-hop da…
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection
Zhihao Ding, Jieming Shi, Shiqi Shen +4
Graph-level representation learning is important in a wide range of applications. Existing graph-level models are generally built on i.i.d. assumption for both training and testing…
Effective Illicit Account Detection on Large Cryptocurrency MultiGraphs
Zhihao Ding, Jieming Shi, Qing Li +1
Cryptocurrencies are rapidly expanding and becoming vital in digital financial markets. However, the rise in cryptocurrency-related illicit activities has led to significant losses…