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Yuxin Wang

15 papers hereh-index 574 citations21 works total

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

author position
  • first author5
  • middle author9
  • last author1

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • cs.CL7
  • cs.LG4
  • cs.AI3
  • cs.SE1
same name
  • Yuxin Wang — 20 papers, h 12
  • Yuxin Wang — 16 papers, h 18
  • Yuxin Wang — 14 papers, h 4
  • Yuxin Wang — 12 papers, h 3
  • Yuxin Wang — 9 papers, h 8
  • Yuxin Wang — 9 papers, h 11

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 citedEfficient Link Prediction via GNN Layers Induced by Negative Sampling

19 citations · 19 across the 15 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

ABOPD: Antibody CDR Design via On-Policy Distillation

Zhuo Yang, Jiaying He, Jiaqing Xie +5

Antibodies are essential therapeutic molecules, and their complementarity-determining regions (CDRs) form the primary antigen-recognition interface. Recent protein generative model…

cs.LG2026

Eigenbasis-Independent Learnable Spectral Positional Encodings for Directed Graphs via Hermitian Block Krylov Subspaces

Jiaqing Xie, Yuxin Wang

Spectral positional encodings (PEs) for \emph{directed} graphs face two obstacles: magnetic Laplacians require an O(n3) Hermitian eigendecomposition per potential, and their com…

cs.LG2025

Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners

Yuxin Wang, Botian Jiang, Yiran Guo +4

Prior-Fitted Networks (PFNs) have recently been proposed to efficiently perform tabular classification tasks. Although they achieve good performance on small datasets, they encount…

cs.LG2023★ 19 cited

Efficient Link Prediction via GNN Layers Induced by Negative Sampling

Yuxin Wang, Xiannian Hu, Quan Gan +3

Graph neural networks (GNNs) for link prediction can loosely be divided into two broad categories. First, \emph{node-wise} architectures pre-compute individual embeddings for each…

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