activity
20222025
most citedConsRec: Learning Consensus Behind Interactions for Group Recommendation

49 citations · 102 across the 14 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.SI2024

ProCom: A Few-shot Targeted Community Detection Algorithm

Xixi Wu, Kaiyu Xiong, Yun Xiong +4

Targeted community detection aims to distinguish a particular type of community in the network. This is an important task with a lot of real-world applications, e.g., identifying f…

cs.LG2024

DTFormer: A Transformer-Based Method for Discrete-Time Dynamic Graph Representation Learning

Xi Chen, Yun Xiong, Siwei Zhang +7

Discrete-Time Dynamic Graphs (DTDGs), which are prevalent in real-world implementations and notable for their ease of data acquisition, have garnered considerable attention from bo…

cs.SI2024

Towards Adaptive Neighborhood for Advancing Temporal Interaction Graph Modeling

Siwei Zhang, Xi Chen, Yun Xiong +5

Temporal Graph Networks (TGNs) have demonstrated their remarkable performance in modeling temporal interaction graphs. These works can generate temporal node representations by enc…

cs.LG2024★ 2 cited

Can Graph Learning Improve Planning in LLM-based Agents?

Xixi Wu, Yifei Shen, Caihua Shan +8

Task planning in language agents is emerging as an important research topic alongside the development of large language models (LLMs). It aims to break down complex user requests i…

cs.LG2024

Beyond the Known: Novel Class Discovery for Open-world Graph Learning

Yucheng Jin, Yun Xiong, Juncheng Fang +5

Node classification on graphs is of great importance in many applications. Due to the limited labeling capability and evolution in real-world open scenarios, novel classes can emer…

cs.AI2024★ 1 cited

Prompt Learning on Temporal Interaction Graphs

Xi Chen, Siwei Zhang, Yun Xiong +6

Temporal Interaction Graphs (TIGs) are widely utilized to represent real-world systems. To facilitate representation learning on TIGs, researchers have proposed a series of TIG mod…

q-bio.BM2024

DDIPrompt: Drug-Drug Interaction Event Prediction based on Graph Prompt Learning

Yingying Wang, Yun Xiong, Xixi Wu +2

Drug combinations can cause adverse drug-drug interactions(DDIs). Identifying specific effects is crucial for developing safer therapies. Previous works on DDI event prediction hav…