Heterogeneous Node Classification

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

7 leaderboard tables shown for this task, 7 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

8 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

14 shown of 14 papers with code (16 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Graph Attention Networks
  30 Oct 2017 93 repositories listed Syntology ran 50 of 106 samples · 56 unverified · 43 pointer-only (licence)
  We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph…
• Semi-Supervised Classification with Graph Convolutional Networks
  9 Sep 2016 55 repositories listed Syntology ran 31 of 58 samples · 27 unverified · 22 pointer-only (licence)
  We present a scalable approach for semi-supervised learning on graph-structured data that is based on an efficient variant of convolutional neural networks which operate directly on graphs.
• Modeling Relational Data with Graph Convolutional Networks
  17 Mar 2017 27 repositories listed Syntology ran 10 of 32 samples · 22 unverified · 15 pointer-only (licence)
  We demonstrate the effectiveness of R-GCNs as a stand-alone model for entity classification.
• Heterogeneous Graph Transformer
  3 Mar 2020 4 repositories listed Syntology ran 1 of 6 samples · 5 unverified
  Recent years have witnessed the emerging success of graph neural networks (GNNs) for modeling structured data.
• Simple and Efficient Heterogeneous Graph Neural Network
  6 Jul 2022 2 repositories listed
  Heterogeneous graph neural networks (HGNNs) have powerful capability to embed rich structural and semantic information of a heterogeneous graph into node representations.
• Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks
  30 Dec 2021 2 repositories listed
  Heterogeneous graph neural networks (HGNNs) have been blossoming in recent years, but the unique data processing and evaluation setups used by each work obstruct a full understanding of their advancements.
• From Primes to Paths: Enabling Fast Multi-Relational Graph Analysis
  17 Nov 2024 1 repository listed
  This enables a compact representation of a complete multi-relational graph using a single adjacency matrix, which, in turn, facilitates quick computation of multi-hop adjacency matrices.
• SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network
  3 May 2024 1 repository listed Syntology ran 6 of 7 samples · 1 unverified
  We identify a potential semantic mixing issue in existing message passing processes, where the representations of the neighbors of a node v are forced to be transformed to the feature space of v for aggregation, though…
• Efficient Heterogeneous Graph Learning via Random Projection
  23 Oct 2023 1 repository listed Syntology ran 5 of 8 samples · 3 unverified · 8 pointer-only (licence)
  To achieve low information loss, we introduce a Relation-wise Neighbor Collection component with an Even-odd Propagation Scheme, which aims to collect information from neighbors in a finer-grained way.
• Scalable Graph Neural Networks for Heterogeneous Graphs
  19 Nov 2020 1 repository listed
  Graph neural networks (GNNs) are a popular class of parametric model for learning over graph-structured data.
• An Attention-based Graph Neural Network for Heterogeneous Structural Learning
  19 Dec 2019 1 repository listed Syntology ran 0 of 3 samples · 3 unverified
  In this paper, we focus on graph representation learning of heterogeneous information network (HIN), in which various types of vertices are connected by various types of relations.
• Non-local Attention Learning on Large Heterogeneous Information Networks
  12 Dec 2019 1 repository listed
  In this way, it leverages both local and non-local information simultaneously.
• Heterogeneous Deep Graph Infomax
  19 Nov 2019 1 repository listed
  The derived node representations can be used to serve various downstream tasks, such as node classification and node clustering.
• Graph Transformer Networks
  6 Nov 2019 1 repository listed
  In this paper, we propose Graph Transformer Networks (GTNs) that are capable of generating new graph structures, which involve identifying useful connections between unconnected nodes on the original graph, while…

Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.