Graph Similarity

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 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

3 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.

Most implemented papers archive 2025-07-28

30 shown of 51 papers with code (113 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.

• clDice -- A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
  16 Mar 2020 4 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 1 pointer-only (licence)
  Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research.
• SimGNN: A Neural Network Approach to Fast Graph Similarity Computation
  16 Aug 2018 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  Our model achieves better generalization on unseen graphs, and in the worst case runs in quadratic time with respect to the number of nodes in two graphs.
• Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks
  7 Mar 2017 3 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  Evaluating similarity between graphs is of major importance in several computer vision and pattern recognition problems, where graph representations are often used to model objects or interactions between elements.
• GREED: A Neural Framework for Learning Graph Distance Functions
  24 Dec 2021 2 repositories listed Syntology ran 2 of 15 samples · 13 unverified
  To elaborate, although GED is a metric, its neural approximations do not provide such a guarantee.
• SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
  21 May 2025 1 repository listed
  Despite the dominance of convolutional and transformer-based architectures in image-to-image retrieval, these models are prone to biases arising from low-level visual features, such as color.
• HeGMN: Heterogeneous Graph Matching Network for Learning Graph Similarity
  11 Mar 2025 1 repository listed
  Graph similarity learning (GSL), also referred to as graph matching in many scenarios, is a fundamental problem in computer vision, pattern recognition, and graph learning.
• Quality Measures for Dynamic Graph Generative Models
  3 Mar 2025 1 repository listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)
  This results in an expressive, scalar, and application-agnostic measure of dynamic graph similarity that overcomes the limitations of traditional methods.
• Neural Network Graph Similarity Computation Based on Graph Fusion
  25 Feb 2025 1 repository listed
  By merging the node sequences of graph pairs into a single large graph, our method leverages a global attention mechanism to facilitate interaction computations and to harvest cross-graph insights.
• GraSP: Simple yet Effective Graph Similarity Predictions
  13 Dec 2024 1 repository listed
  In GSC, graph edit distance (GED) and maximum common subgraph (MCS) are two important similarity metrics, both of which are NP-hard to compute.
• Covered Forest: Fine-grained generalization analysis of graph neural networks
  10 Dec 2024 1 repository listed Syntology ran 1 of 7 samples · 6 unverified
  The expressive power of message-passing graph neural networks (MPNNs) is reasonably well understood, primarily through combinatorial techniques from graph isomorphism testing.
• Efficient Graph Similarity Computation with Alignment Regularization
  21 Jun 2024 1 repository listed Syntology ran 12 of 16 samples · 4 unverified · 16 pointer-only (licence)
  In the inference stage, the graph-level representations learned by the GNN encoder are directly used to compute the similarity score without using AReg again to speed up inference.
• S^2MVTC: a Simple yet Efficient Scalable Multi-View Tensor Clustering
  14 Mar 2024 1 repository listed
  Specifically, we first construct the embedding feature tensor by stacking the embedding features of different views into a tensor and rotating it.
• Structure Your Data: Towards Semantic Graph Counterfactuals
  11 Mar 2024 1 repository listed Syntology ran 8 of 11 samples · 3 unverified · 11 pointer-only (licence)
  With a focus on the visual domain, we represent images as scene graphs and obtain their GNN embeddings to bypass solving the NP-hard graph similarity problem for all input pairs, an integral part of the CE computation…
• S2MVTC: a Simple yet Efficient Scalable Multi-View Tensor Clustering
  1 Jan 2024 1 repository listed
  Specifically we first construct the embedding feature tensor by stacking the embedding features of different views into a tensor and rotating it.
• Do Similar Entities have Similar Embeddings?
  16 Dec 2023 1 repository listed
  A common tacit assumption is the KGE entity similarity assumption, which states that these KGEMs retain the graph's structure within their embedding space, \textit{i.
• MATA*: Combining Learnable Node Matching with A* Algorithm for Approximate Graph Edit Distance Computation
  4 Nov 2023 1 repository listed
  Graph Edit Distance (GED) is a general and domain-agnostic metric to measure graph similarity, widely used in graph search or retrieving tasks.
• FACTUAL: A Benchmark for Faithful and Consistent Textual Scene Graph Parsing
  27 May 2023 1 repository listed
  Textual scene graph parsing has become increasingly important in various vision-language applications, including image caption evaluation and image retrieval.
• Towards Writer Retrieval for Historical Datasets
  9 May 2023 1 repository listed
  Our approach is evaluated on two historical datasets (Historical-WI and HisIR19).
• Dynamic Vertex Replacement Grammars
  21 Mar 2023 1 repository listed
  Context-free graph grammars have shown a remarkable ability to model structures in real-world relational data.
• Compressed Heterogeneous Graph for Abstractive Multi-Document Summarization
  12 Mar 2023 1 repository listed
  We propose HGSUM, an MDS model that extends an encoder-decoder architecture, to incorporate a heterogeneous graph to represent different semantic units (e.
• Learning Feature Recovery Transformer for Occluded Person Re-identification
  5 Jan 2023 1 repository listed
  To reduce the interference of the noise during feature matching, we mainly focus on visible regions that appear in both images and develop a visibility graph to calculate the similarity.
• Joint graph learning from Gaussian observations in the presence of hidden nodes
  4 Dec 2022 1 repository listed
  Motivated by this, we propose a joint graph learning method that takes into account the presence of hidden (latent) variables.
• Privacy-Preserved Neural Graph Similarity Learning
  21 Oct 2022 1 repository listed
  To develop effective and efficient graph similarity learning (GSL) models, a series of data-driven neural algorithms have been proposed in recent years.
• Beyond Supervised vs. Unsupervised: Representative Benchmarking and Analysis of Image Representation Learning
  16 Jun 2022 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  In this paper, we compare methods using performance-based benchmarks such as linear evaluation, nearest neighbor classification, and clustering for several different datasets, demonstrating the lack of a clear…
• CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning
  30 May 2022 1 repository listed
  As most of the existing graph neural networks yield effective graph representations of a single graph, little effort has been made for jointly learning two graph representations and calculating their similarity score.
• Graph similarity learning for change-point detection in dynamic networks
  29 Mar 2022 1 repository listed
  The main novelty of our method is to use a siamese graph neural network architecture for learning a data-driven graph similarity function, which allows to effectively compare the current graph and its recent history.
• Weisfeiler-leman in the bamboo: Novel AMR graph metrics and a benchmark for AMR graph similarity.
  4 Jan 2022 1 repository listed
  In this work we propose new Weisfeiler-Leman AMR similarity metrics that unify the strengths of previous metrics, while mitigating their weaknesses.
• Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning
  16 Dec 2021 1 repository listed
  Hence, this work proposes a new principle for unsupervised graph representation learning: Graph-wise Common latent Factor EXtraction (GCFX).
• Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
  1 Dec 2021 1 repository listed
  For slow learning of graph similarity, this paper proposes a novel early-fusion approach by designing a co-attention-based feature fusion network on multilevel GNN features.
• clDice - A Novel Topology-Preserving Loss Function for Tubular Structure Segmentation
  19 Jun 2021 1 repository listed
  Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research.

Syntology lines on 9 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.