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A3. Deepfake

[2025/04] SafeSpeech: Robust and Universal Voice Protection Against Malicious Speech Synthesis
[2025/03] SoK: How Robust is Audio Watermarking in Generative AI models?
[2025/03] Detecting LLM-Written Peer Reviews
[2025/03] TH-Bench: Evaluating Evading Attacks via Humanizing AI Text on Machine-Generated Text Detecto
[2025/02] Iron Sharpens Iron: Defending Against Attacks in Machine-Generated Text Detection with Adversarial Training
[2025/02] FaceSwapGuard: Safeguarding Facial Privacy from DeepFake Threats through Identity Obfuscation
[2025/02] PDA: Generalizable Detection of AI-Generated Images via Post-hoc Distribution Alignment
[2025/02] GAP-Diff: Protecting JPEG-Compressed Images from Diffusion-based Facial Customization
[2025/02] Modification and Generated-Text Detection: Achieving Dual Detection Capabilities for the Outputs of LLM by Watermark
[2025/01] FDLLM: A Text Fingerprint Detection Method for LLMs in Multi-Language, Multi-Domain Black-Box Environments
[2024/12] Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media
[2024/11] Passive Deepfake Detection Across Multi-modalities: A Comprehensive Survey
[2024/11] AI-generated Image Detection: Passive or Watermark?
[2024/11] A Quality-Centric Framework for Generic Deepfake Detection
[2024/10] Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors
[2024/10] Characterizing the MrDeepFakes Sexual Deepfake Marketplace
[2024/10] Social Media Authentication and Combating Deepfakes using Semi-fragile Invisible Image Watermarking
[2024/09] FIDAVL: Fake Image Detection and Attribution using Vision-Language Model
[2024/09] LLM Detectors Still Fall Short of Real World: Case of LLM-Generated Short News-Like Posts
[2024/08] MAGE: Machine-generated Text Detection in the Wild
[2024/08] Are AI-Generated Text Detectors Robust to Adversarial Perturbations?
[2024/08] Event-Radar: Event-driven Multi-View Learning for Multimodal Fake News Detection
[2024/08] Unveiling Opinion Evolution via Prompting and Diffusion for Short Video Fake News Detection
[2024/06] Investigating the Influence of Prompt-Specific Shortcuts in AI Generated Text Detection
[2024/06] Applying Ensemble Methods to Model-Agnostic Machine-Generated Text Detection
[2024/06] Evading AI-Generated Content Detectors using Homoglyphs
[2024/06] Are AI-Generated Text Detectors Robust to Adversarial Perturbations?
[2024/05] Transformer and Hybrid Deep Learning Based Models for Machine-Generated Text Detection
[2024/05] RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors
[2024/05] Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScore
[2024/04] An Analysis of Recent Advances in Deepfake Image Detection in an Evolving Threat Landscape
[2024/04] The Adversarial AI-Art: Understanding, Generation, Detection, and Benchmarking
[2024/04] DeepFake-O-Meter v2.0: An Open Platform for DeepFake Detection
[2024/04] Watermark-based Detection and Attribution of AI-Generated Content
[2024/04] Humanizing Machine-Generated Content: Evading AI-Text Detection through Adversarial Attack
[2024/03] Can ChatGPT Detect DeepFakes? A Study of Using Multimodal Large Language Models for Media Forensics
[2024/03] The Impact of Prompts on Zero-Shot Detection of AI-Generated Text
[2024/03] Quantitative Analysis of AI-Generated Texts in Academic Research: A Study of AI Presence in Arxiv Submissions using AI Detection Tool
[2024/03] Re-Search for The Truth: Multi-round Retrieval-augmented Large Language Models are Strong Fake News Detectors
[2024/03] GPT-generated Text Detection: Benchmark Dataset and Tensor-based Detection Method
[2024/03] Towards Detecting AI-Generated Text within Human-AI Collaborative Hybrid Texts
[2024/03] A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization
[2024/02] Technical Report on the Checkfor.ai AI-Generated Text Classifier
[2024/02] VGMShield: Mitigating Misuse of Video Generative Models
[2024/02] M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detection
[2024/02] Ten Words Only Still Help: Improving Black-Box AI-Generated Text Detection via Proxy-Guided Efficient Re-Sampling
[2024/02] Does DETECTGPT Fully Utilize Perturbation? Selective Perturbation on Model-Based Contrastive Learning Detector would be Better
[2024/02] TELLER: A Trustworthy Framework for Explainable, Generalizable and Controllable Fake News Detection
[2024/02] Organic or Diffused: Can We Distinguish Human Art from AI-generated Images?
[2024/01] Raidar: geneRative AI Detection viA Rewriting
[2024/01] Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
[2024/01] Enhancing Robustness of LLM-Synthetic Text Detectors for Academic Writing: A Comprehensive Analysis
[2024/01] Authorship Obfuscation in Multilingual Machine-Generated Text Detection
[2024/01] Few-Shot Detection of Machine-Generated Text using Style Representations
[2024/01] LLM-as-a-Coauthor: The Challenges of Detecting LLM-Human Mixcase
[2023/10] Harnessing the Power of ChatGPT in Fake News: An In-Depth Exploration in Generation, Detection and Explanation
[2023/09] Can LLM-Generated Misinformation be Detected?
[2023/09] Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
[2023/09] Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
[2023/06] On the Detectability of ChatGPT Content: Benchmarking, Methodology, and Evaluation through the Lens of Academic Writing
[2023/05] On the Risk of Misinformation Pollution with Large Language Models
[2023/05] Evading Watermark based Detection of AI-Generated Content
[2023/04] Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions
[2023/03] Can AI-Generated Text be Reliably Detected?
[2023/03] MGTBench: Benchmarking Machine-Generated Text Detection
[2022/12] Discovering Language Model Behaviors with Model-Written Evaluations
[2022/12] CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Data Limitation With Contrastive Learning
[2022/10] DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Generation Models