activity
20192026
most citedMulti-modal Deep Analysis for Multimedia

59 citations · 93 across the 14 of their papers we have counts for

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Showing cs.LGShow all

13 papers · 1 filter

cs.LG2026

OOD-GraphLLM: Graph Large Language Model for Out-of-Distribution Generalized Drug Synergy Prediction

Xin Wang, Linxin Xiao, Yang Yao +1

Drug synergy prediction (DSP) aims to identify efficacious drug combinations under various cellular contexts with different targets. However, the continual emergence of novel compo…

cs.LG2026

A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning

Haibo Chen, Xin Wang, Jiaheng Chao +2

Leveraging Graph Neural Networks (GNNs) as graph encoders and aligning the resulting representations with Large Language Models (LLMs) through alignment instruction tuning has beco…

cs.LG20242 cited

Exploring the Potential of Large Language Models in Graph Generation

Yang Yao, Xin Wang, Zeyang Zhang +6

Large language models (LLMs) have achieved great success in many fields, and recent works have studied exploring LLMs for graph discriminative tasks such as node classification. Ho…

cs.LG20243 cited

Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision

Zeyang Zhang, Xin Wang, Ziwei Zhang +3

The existing graph neural architecture search (GNAS) methods heavily rely on supervised labels during the search process, failing to handle ubiquitous scenarios where supervisions…

cs.LG20243 cited

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts

Zeyang Zhang, Xin Wang, Ziwei Zhang +5

Dynamic graph neural networks (DyGNNs) currently struggle with handling distribution shifts that are inherent in dynamic graphs. Existing work on DyGNNs with out-of-distribution se…

cs.LG2023

Out-of-Distribution Generalized Dynamic Graph Neural Network for Human Albumin Prediction

Zeyang Zhang, Xingwang Li, Fei Teng +4

Human albumin is essential for indicating the body's overall health. Accurately predicting plasma albumin levels and determining appropriate doses are urgent clinical challenges, p…