{"total":22,"rows":[{"id":"2108.05080","title":"FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset","created":"2021-08-11","cited_by_count":181,"area":null},{"id":"2503.02857","title":"Deepfake-Eval-2024: A Multi-Modal In-the-Wild Benchmark of Deepfakes Circulated in 2024","created":"2025-03-04","cited_by_count":45,"area":null},{"id":"2109.02993","title":"Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors","created":"2021-09-07","cited_by_count":32,"area":null},{"id":"2401.04364","title":"SoK: Systematization and Benchmarking of Deepfake Detectors in a Unified Framework","created":"2024-01-09","cited_by_count":14,"area":null},{"id":"2303.06280","title":"Stateful Defenses for Machine Learning Models Are Not Yet Secure Against Black-box Attacks","created":"2023-03-11","cited_by_count":11,"area":null},{"id":"2407.12876","title":"Exploring the Use of Abusive Generative AI Models on Civitai","created":"2024-07-16","cited_by_count":10,"area":null},{"id":"2212.00773","title":"FakeOut: Leveraging Out-of-domain Self-supervision for Multi-modal Video Deepfake Detection","created":"2022-12-01","cited_by_count":8,"area":null},{"id":"2402.01721","title":"Non-Consensual Synthetic Intimate Imagery: Prevalence, Attitudes, and Knowledge in 10 Countries","created":"2024-01-26","cited_by_count":8,"area":null},{"id":"2204.12816","title":"The MeVer DeepFake Detection Service: Lessons Learnt from Developing and Deploying in the Wild","created":"2022-04-27","cited_by_count":6,"area":null},{"id":"2208.10913","title":"Deepfake: Definitions, Performance Metrics and Standards, Datasets and Benchmarks, and a Meta-Review","created":"2022-08-21","cited_by_count":6,"area":null},{"id":"2212.14033","title":"How Do Deepfakes Move? Motion Magnification for Deepfake Source Detection","created":"2022-12-28","cited_by_count":5,"area":null},{"id":"2210.03683","title":"Quantitative Metrics for Evaluating Explanations of Video DeepFake Detectors","created":"2022-10-07","cited_by_count":3,"area":null},{"id":"2410.03487","title":"A Multimodal Framework for Deepfake Detection","created":"2024-10-04","cited_by_count":3,"area":null},{"id":"2507.12232","title":"MGFFD-VLM: Multi-Granularity Prompt Learning for Face Forgery Detection with VLM","created":"2025-07-16","cited_by_count":3,"area":null},{"id":"2203.05178","title":"An Audio-Visual Attention Based Multimodal Network for Fake Talking Face Videos Detection","created":"2022-03-10","cited_by_count":2,"area":null},{"id":"2503.01937","title":"Synthetic Tabular Data Detection In the Wild","created":"2025-03-03","cited_by_count":2,"area":null},{"id":"2307.03990","title":"FTFDNet: Learning to Detect Talking Face Video Manipulation with Tri-Modality Interaction","created":"2023-07-08","cited_by_count":1,"area":null},{"id":"2512.23374","title":"NeXT-IMDL: Build Benchmark for NeXT-Generation Image Manipulation Detection & Localization","created":"2025-12-29","cited_by_count":1,"area":null},{"id":"2408.01668","title":"Multiple Contexts and Frequencies Aggregation Network forDeepfake Detection","created":"2024-08-03","cited_by_count":0,"area":null},{"id":"2412.13227","title":"Cross-table Synthetic Tabular Data Detection","created":"2024-12-17","cited_by_count":0,"area":null},{"id":"2509.04150","title":"Revisiting Simple Baselines for In-The-Wild Deepfake Detection","created":"2025-09-04","cited_by_count":0,"area":null},{"id":"2604.21767","title":"Misinformation Span Detection in Videos via Audio Transcripts","created":"2026-04-23","cited_by_count":0,"area":null}],"next_cursor":null}