Fraud Detection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

12 leaderboard tables shown for this task, 12 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. 10 shown of 12 until expanded.

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

12 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

30 shown of 158 papers with code (547 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.

• Continuous-variable quantum neural networks
  18 Jun 2018 8 repositories listed Syntology ran 2 of 3 samples · 1 unverified
  The quantum neural network is a variational quantum circuit built in the continuous-variable (CV) architecture, which encodes quantum information in continuous degrees of freedom such as the amplitudes of the…
• SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training
  2 Jun 2021 7 repositories listed Syntology ran 3 of 26 samples · 23 unverified · 13 pointer-only (licence)
  We devise a hybrid deep learning approach to solving tabular data problems.
• Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
  19 Aug 2020 6 repositories listed Syntology ran 1 of 17 samples · 16 unverified
  Finally, the selected neighbors across different relations are aggregated together.
• Deep Anomaly Detection with Deviation Networks
  19 Nov 2019 6 repositories listed
  Instead of representation learning, our method fulfills an end-to-end learning of anomaly scores by a neural deviation learning, in which we leverage a few (e.
• Grad: Guided Relation Diffusion Generation for Graph Augmentation in Graph Fraud Detection
  22 Apr 2025 3 repositories listed
  Specifically, fraudsters disguise themselves by mimicking the behavioral data collected by platforms, ensuring that their key characteristics are consistent with those of benign users to a high degree, which we call…
• EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements
  10 Jun 2025 2 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  To address this gap, we introduce EDINET-Bench, an open-source Japanese financial benchmark designed to evaluate the performance of LLMs on challenging financial tasks including accounting fraud detection, earnings…
• Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation
  24 Dec 2024 2 repositories listed
  Then we pass messages among the nodes through a Gated Temporal Attention Network (GTAN) to learn the transaction representation.
• AD-LLM: Benchmarking Large Language Models for Anomaly Detection
  15 Dec 2024 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Anomaly detection (AD) is an important machine learning task with many real-world uses, including fraud detection, medical diagnosis, and industrial monitoring.
• SplitGNN: Spectral Graph Neural Network for Fraud Detection against Heterophily
  21 Oct 2023 2 repositories listed
  However, researches on addressing the heterophily problem in the spectral domain are still limited due to a lack of understanding of spectral energy distribution in graphs with heterophily.
• GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction
  2 Jun 2023 2 repositories listed
  Graph Anomaly Detection (GAD) is a technique used to identify abnormal nodes within graphs, finding applications in network security, fraud detection, social media spam detection, and various other domains.
• BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware
  30 Mar 2023 2 repositories listed
  Efficient large-scale neural network training and inference on commodity CPU hardware is of immense practical significance in democratizing deep learning (DL) capabilities.
• Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation
  24 Nov 2022 2 repositories listed Syntology ran 0 of 9 samples · 9 unverified
  The suite was generated by applying state-of-the-art tabular data generation techniques on an anonymized, real-world bank account opening fraud detection dataset.
• Fraud Dataset Benchmark and Applications
  30 Aug 2022 2 repositories listed
  Standardized datasets and benchmarks have spurred innovations in computer vision, natural language processing, multi-modal and tabular settings.
• Crypto Pump and Dump via Deep Learning Techniques
  10 May 2022 2 repositories listed
  Despite the fact that cryptocurrencies themselves have experienced an astonishing rate of adoption over the last decade, cryptocurrency fraud detection is a heavily under-researched problem area.
• TOD: GPU-accelerated Outlier Detection via Tensor Operations
  26 Oct 2021 2 repositories listed Syntology ran 0 of 10 samples · 10 unverified
  Outlier detection (OD) is a key learning task for finding rare and deviant data samples, with many time-critical applications such as fraud detection and intrusion detection.
• How effective are Graph Neural Networks in Fraud Detection for Network Data?
  30 May 2021 2 repositories listed
  Among these patterns, financial fraud stands out for its socioeconomic relevance and for presenting particular challenges, such as the extreme imbalance between the positive (fraud) and negative (legitimate…
• Promoting Fairness through Hyperparameter Optimization
  23 Mar 2021 2 repositories listed
  Considerable research effort has been guided towards algorithmic fairness but real-world adoption of bias reduction techniques is still scarce.
• Graph Prototypical Networks for Few-shot Learning on Attributed Networks
  23 Jun 2020 2 repositories listed
  By constructing a pool of semi-supervised node classification tasks to mimic the real test environment, GPN is able to perform \textit{meta-learning} on an attributed network and derive a highly generalizable model for…
• The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure
  9 Oct 2019 2 repositories listed
  a statistical population may play a crucial role in this regard, anomalies corresponding to observations with 'small' depth.
• Credit Card Fraud Detection Using Autoencoder Neural Network
  30 Aug 2019 2 repositories listed
  Imbalanced data classification problem has always been a popular topic in the field of machine learning research.
• GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering
  4 Jun 2025 1 repository listed
  Money laundering poses a significant challenge as it is estimated to account for 2%-5% of the global GDP.
• AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection
  19 May 2025 1 repository listed
  Anomaly detection (AD) is essential in areas such as fraud detection, network monitoring, and scientific research.
• Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets
  7 May 2025 1 repository listed
  Therefore, we recommend testing single classifiers and imbalance learning techniques for each new dataset and application involving imbalanced datasets as is the case in several cyber security applications.
• Federated Spectral Graph Transformers Meet Neural Ordinary Differential Equations for Non-IID Graphs
  16 Apr 2025 1 repository listed
  Our results in the area of federated learning on non-IID heterophilic graphs demonstrate significant improvements, while also achieving better performance on homophilic graphs.
• FeatInsight: An Online ML Feature Management System on 4Paradigm Sage-Studio Platform
  1 Apr 2025 1 repository listed
  Feature management is essential for many online machine learning applications and can often become the performance bottleneck (e.
• TeleAntiFraud-28k: An Audio-Text Slow-Thinking Dataset for Telecom Fraud Detection
  31 Mar 2025 1 repository listed
  The detection of telecom fraud faces significant challenges due to the lack of high-quality multimodal training data that integrates audio signals with reasoning-oriented textual analysis.
• Financial Fraud Detection with Entropy Computing
  14 Mar 2025 1 repository listed
  We introduce CVQBoost, a novel classification algorithm that leverages early hardware implementing Quantum Computing Inc's Entropy Quantum Computing (EQC) paradigm, Dirac-3 [Nguyen et.
• Corporate Fraud Detection in Rich-yet-Noisy Financial Graph
  26 Feb 2025 1 repository listed
  Corporate fraud detection aims to automatically recognize companies that conduct wrongful activities such as fraudulent financial statements or illegal insider trading.
• Pub-Guard-LLM: Detecting Fraudulent Biomedical Articles with Reliable Explanations
  21 Feb 2025 1 repository listed
  We propose Pub-Guard-LLM, the first large language model-based system tailored to fraud detection of biomedical scientific articles.
• A Label-Free Heterophily-Guided Approach for Unsupervised Graph Fraud Detection
  18 Feb 2025 1 repository listed Syntology ran 1 of 10 samples · 9 unverified
  In the alignment-based fraud detection module, we develop a joint MLP-GNN architecture with ranking loss and asymmetric alignment loss.

Syntology lines on 8 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.