5 papers · 1 filter
ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design
Yulin Zhang, He Cao, Zihao Jiang +6
Designing proteins with desired functions or properties represents a core goal in synthetic biology and drug discovery. Recent advances in protein language models (PLMs) have enabl…
A Survey of Cross-domain Graph Learning: Progress and Future Directions
Haihong Zhao, Zhixun Li, Chenyi Zi +4
Graph learning plays a vital role in mining and analyzing complex relationships within graph data and has been widely applied to real-world scenarios such as social, citation, and…
UniGAD: Unifying Multi-level Graph Anomaly Detection
Yiqing Lin, Jianheng Tang, Chenyi Zi +3
Graph Anomaly Detection (GAD) aims to identify uncommon, deviated, or suspicious objects within graph-structured data. Existing methods generally focus on a single graph object typ…
ProG: A Graph Prompt Learning Benchmark
Chenyi Zi, Haihong Zhao, Xiangguo Sun +3
Artificial general intelligence on graphs has shown significant advancements across various applications, yet the traditional 'Pre-train & Fine-tune' paradigm faces inefficiencies…
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment
Haihong Zhao, Chenyi Zi, Yang Liu +3
Anomaly detection (AD) plays a pivotal role in numerous web-based applications, including malware detection, anti-money laundering, device failure detection, and network fault anal…