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Wei Jin

33 papers hereh-index 274.8k citations50 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author11
  • middle author20

Across the 31 of 33 papers where every author was matched, so the position is known.

fields
  • cs.LG25
  • cs.IR4
  • q-bio.GN2
  • cs.CL1
  • q-bio.QM1
same name
  • Wei Jin — 10 papers, h 6
  • Wei Jin — 7 papers, h 5
  • Wei Jin — 6 papers, h 1
  • Wei Jin — 5 papers, h 3
  • Wei Jin — 4 papers, h 2
  • Wei Jin — 4 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedSelf-supervised Learning on Graphs: Deep Insights and New Direction

111 citations · 717 across the 33 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

Sub-graph Based Diffusion Model for Link Prediction

Hang Li, Wei Jin, Geri Skenderi +4

Denoising Diffusion Probabilistic Models (DDPMs) represent a contemporary class of generative models with exceptional qualities in both synthesis and maximizing the data likelihood…

cs.LG2024★ 1 cited

Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness

Kai Guo, Zewen Liu, Zhikai Chen +4

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language processing tasks. Recently, several LLMs-based pipelines have been developed t…

cs.IR2024

Enhancing ID and Text Fusion via Alternative Training in Session-based Recommendation

Juanhui Li, Haoyu Han, Zhikai Chen +4

Session-based recommendation has gained increasing attention in recent years, with its aim to offer tailored suggestions based on users' historical behaviors within sessions. To ad…

cs.LG2024

Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective

Kai Guo, Hongzhi Wen, Wei Jin +3

Graph neural networks (GNNs) have exhibited remarkable performance under the assumption that test data comes from the same distribution of training data. However, in real-world sce…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.