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Mengzhu Wang

14 papers hereh-index 6159 citations25 works total

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

author position
  • first author1
  • middle author12

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.CV3
  • cs.CL2
  • cs.NE2
  • cs.AI1
same name
  • Mengzhu Wang — 4 papers, h 9
  • Mengzhu Wang — 4 papers, h 2
  • Mengzhu Wang — 4 papers, h 1
  • Mengzhu Wang — 3 papers, h 2
  • Mengzhu Wang — 2 papers, h 0
  • Mengzhu Wang — 2 papers, h 0

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
20232026
most citedContinuous Spiking Graph Neural Networks

2 citations · 5 across the 14 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CL2026

TRACE: An Experiential Framework for Coherent Multi-hop Knowledge Graph Question Answering

Yingxu Wang, Jiaxin Huang, Mengzhu Wang +1

Multi-hop Knowledge Graph Question Answering (KGQA) requires coherent reasoning across relational paths, yet existing methods often treat each reasoning step independently and fail…

cs.LG2026

DSBD: Dual-Aligned Structural Basis Distillation for Graph Domain Adaptation

Yingxu Wang, Kunyu Zhang, Jiaxin Huang +4

Graph domain adaptation (GDA) aims to transfer knowledge from a labeled source graph to an unlabeled target graph under distribution shifts. However, existing methods are largely f…

cs.LG2026

USBD: Universal Structural Basis Distillation for Source-Free Graph Domain Adaptation

Yingxu Wang, Kunyu Zhang, Mengzhu Wang +2

SF-GDA is pivotal for privacy-preserving knowledge transfer across graph datasets. Although recent works incorporate structural information, they implicitly condition adaptation on…

cs.LG2026

DisRFM: Polar Riemannian Flow Matching for Structure-Preserving Graph Domain Adaptation

Yingxu Wang, Xinwang Liu, Mengzhu Wang +2

Graph Domain Adaptation (GDA) aims to transfer graph classifiers across domains with both semantic and topological shifts. Existing Euclidean adversarial methods face two challenge…

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