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Deepfakes & multimodalDatasets & evaluation DeepfakeGenome: Toward Next-Generation Deepfake AttributionDeepfakeGenome (DFG) is a large-scale benchmark for deepfake detection and attribution covering 100 facial forgery algorithms and 2M images — 4–100× larger than prior benchmarks. The paper proposes 4 evaluation protocols using novel retrieval-based attribution metrics (mAP, Recall) instead of reject-class classification, and conducts… Wang et al. · NeurIPS 2026 · 2026

Deepfakes & multimodalDetection methods UniGADD: Universal Generator-Agnostic Deepfake DetectorUniGADD proposes a two-stage supervised contrastive learning framework for detecting deepfakes from previously unseen generators. The method learns discriminative embeddings from known fake generators in stage one, then refines cluster structure via intra-cluster compactness constraints in stage two. Tomczyk et al. · arXiv · 2026

Deepfakes & multimodalDetection methods ReplayFactor: Replay-Aware Dual-Attribute Learning for Practical Speech Deepfake DetectionExisting speech deepfake detectors fail on physically replayed synthetic speech (played through a loudspeaker and re-recorded), a low-cost, practical threat to voice authentication systems. ReplayFactor addresses this by learning both source authenticity (human vs. generated) and replay presence (non-replayed vs. replayed) via SSL-based… He et al. · arXiv · 2026

LLMs & generative AIDatasets & evaluation The uneven rise of AI-generated web contentAnalyzing 5+ million webpages from 2019–2026, this work documents that AI-generated text prevalence rose from ~2% to nearly 25% by August 2026, with uneven adoption across the web. Growth is concentrated in peripheral, poorly-connected domains rather than central platforms; English-language and .com pages show higher prevalence than .edu… Visokay et al. · arXiv · 2026

Bots & coordinated campaignsDatasets & evaluation Statistical Detectability of CoordinationThis paper formulates coordination detection as a hypothesis-testing problem on account pairs, modeling coordination as a planted submatrix. The authors derive statistical and computational detection limits, test four different null models on 26 information-operation datasets across 7 modalities, and show that multi-modal aggregation is… Iannucci et al. · arXiv · 2026

Fact-checking & verificationPlatforms, policy & society Fact-check? True!: Tracking Verification Requests and the Absence of Truth Verdicts across Correction SystemsExamining 47,899 X/Twitter users asking Grok (X's AI assistant) whether posts are true, the authors find that ~51% of questioned posts are actually accurate, yet correction systems (Community Notes, professional fact-checkers) focus overwhelmingly on false claims. Professional fact-checkers publish true verdicts in only 8–11% of their… Wack & Warren · arXiv · 2026

Platforms, policy & societyDatasets & evaluation Harm Is Behavioural, Moderation Is Lexical: How Language and Culture Decide Whom Automated Safety Systems Protect and Whom They SilenceAutomated content moderation systems recognize harm based on lexical form rather than behavioral function, creating a double inequity: dialects and minority languages face over-flagging while genuine harms (like manipulation tactics) go undetected in under-resourced languages. The paper unifies fairness literature (false positives in… Sabadin et al. · arXiv · 2026

Detection methodsDatasets & evaluation Interpretive Variation and Discourse Structure in Detecting Enthymemes in Controversial Political DiscourseEnthymemes (arguments with unstated premises or conclusions) are a persuasion technique in social media that readers may or may not recognize. This paper develops a DeBERTa-based detector on 1,482 tweets about vaccination and immigration, showing that macro-F1 reaches ~0.67 on hard labels but plateaus due to genuine human disagreement. Pastor & Oostdijk · arXiv · 2026

Platforms, policy & societyDatasets & evaluation When Platforms Pay Users to Correct Misinformation: Revenue Incentives and Governance Capacity in Weibo AnnotationsWeibo Annotations is a crowdsourced governance system that lets users add corrections and contextual information to disputed claims. In May 2025, Weibo introduced monetary rewards for approved annotations. Lin et al. · arXiv · 2026

LLMs & generative AIDetection methods A Large Language Model (LLM) Approach to COVID-19 Fake News DetectionThis paper evaluates seven pre-trained transformer models and LLMs for binary classification of COVID-19 tweets as real or fake using the COVID-19 English Tweets dataset (6,420 tweets). GPT-2 achieves the best performance with 96.31% accuracy and 0.96 F1-score. Arif et al. · arXiv · 2026

Spread & networksDatasets & evaluation Friends as Sensors: High-Sensitivity Monitoring of Misinformation and Platform Dynamics via the Friendship ParadoxThe friendship paradox—a network property where a user's friends are, on average, better connected than the user themselves—enables high-sensitivity monitoring of misinformation on Twitter/X. Comparing ~27 million tweets from randomly selected users to ~31 million from accounts those users retweet (the "sensors"), the authors find: (1)… Angermaier et al. · arXiv · 2026

Bots & coordinated campaignsSpread & networks Birds of a Feather Flock Together: Network-Based Detection of Coordinated Disinformation Campaigns on TelegramA graph-based methodology discovers coordinated disinformation campaigns on Telegram by analyzing message-sharing patterns rather than content, requiring only structural relationships. The authors identified 55 disinformation channels and over 86,000 identical message chains spanning multiple channels, revealing a highly synchronized… Tsagkarakis et al. · SECRYPT · 2026

Platforms, policy & societyDeepfakes & multimodal Drowning in AI Slop: How Social Media Platforms (Do Not) Label AI and Deepfake Content under EU lawThis paper conducts a legally grounded empirical audit of AI-labeling practices across Instagram, TikTok, X, and YouTube, testing how well platforms comply with EU legal obligations to label AI-generated and deepfake content. Using uploads of content generated by 10 generative AI tools, the authors find that platforms labeled only 36 of… Rijsbosch et al. · arXiv · 2026

LLMs & generative AIFact-checking & verification VEX-Bench: Benchmarking Verification Complexity of LLM-Generated MisinformationThis paper introduces VEX-Bench, a unified benchmark for evaluating how difficult it is to verify LLM-generated misinformation. The benchmark measures verification complexity across five dimensions: checkability (whether claims can be checked), harm significance, source credibility signals, impostor legitimacy, and verification cost. Huang et al. · NeurIPS 2026, Track on Evaluations and Datasets · 2026

Bots & coordinated campaignsDatasets & evaluation Setting the clock: Evaluating temporal window parameters for coordinated behavior detectionThe paper systematically evaluates how temporal window parameters (length and stride) affect detection of coordinated communities in co-repost networks. Using 14 labeled information operation datasets, the authors find that window length is a central modeling parameter: short windows (seconds to minutes) detect tight, highly synchronized… Panayiotou et al. · AIDEM Workshop, ECML-PKDD 2026 · 2026

Deepfakes & multimodalDatasets & evaluation VietPrism: A Large-Scale Vietnamese Speech and Deepfake Corpus with Diverse Dialects and Code-SwitchingVIETPRISM is a large-scale Vietnamese speech dataset combining 993.4 hours of bona fide utterances from 1,262 speakers with 3.1K hours of synthetically generated speech from four deepfake systems. The dataset uniquely provides transcripts, dialect annotations, speaker identities, and natural Vietnamese–English code-switching coverage. Hoang & Le · arXiv · 2026

LLMs & generative AIDatasets & evaluation Counter-GEO-Bench: Evaluating Defenses Against Information-Distorting Generative Engine OptimizationAdversaries exploit Generative Engine Optimization (GEO) to craft web documents containing targeted false claims that rank highly in LLM-generated search results. This paper introduces Counter-GEO-Bench, a benchmark of 247 human-verified query-document pairs, evaluates existing guardrails (all ineffective), and proposes C-GEO Guard, a… Zheng et al. · arXiv · 2026

Fact-checking & verificationDatasets & evaluation CoVer: Conflict-Aware Claim VerificationSocial media fact-checking frequently encounters conflicting evidence where different sources support or refute a claim. This paper proposes CoVer, a framework that explicitly resolves evidence-level conflicts (contradictory stances from different sources) and aggregation-level conflicts (sub-claims within complex claims yielding… Zhang et al. · arXiv · 2026

Deepfakes & multimodalDatasets & evaluation MMMMM: A Unified Taxonomy for Investigating the Mechanisms of Multilingual MultiModal MisinformationMultimodal misinformation (images paired with misleading text) is poorly understood compared to text-only fake news, hampered by fragmented taxonomies and the complexity of annotating cross-modal relationships at scale. This work proposes a unified taxonomy of multimodal misinformation mechanisms across six orthogonal axes… Borenstein et al. · arXiv · 2026

LLMs & generative AIFact-checking & verification Calibrating Small Language Models for Claim Check-Worthiness DetectionClaim check-worthiness detection is computationally expensive when using large language models, but essential for scaling fact-checking pipelines. This paper proposes NN-PPI (Nearest Neighbor Prediction-Powered Inference), a post-hoc calibration technique that improves small LM predictions using a small labeled calibration set and… Amatya et al. · arXiv · 2026

LLMs & generative AIDetection methods Build it, Break it, Repeat: Benchmarking and improving LLM-manipulated disinformation detection in social media postsThis paper presents BiBiR (Build-it-Break-it-Repeat), an iterative adversarial benchmarking framework for evaluating machine-generated text detectors under adversarial conditions relevant to social media. Two new datasets enable fine-tuning detectors and testing adversarial robustness. Thomas et al. · arXiv · 2026

Spread & networksDetection methods Network Information Enhances Unreliable News Domain DetectionContent-based detection of unreliable news is increasingly difficult as low-reliability sources mimic credible journalism. The authors show that network structure—how domains co-occur in social networks—can improve news-domain reliability classification. Kefler et al. · arXiv · 2026

Datasets & evaluationDeepfakes & multimodal From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunking in the WildThe paper introduces WildFakeBench, a benchmark of 10,000+ real-world micro-videos spanning diverse misinformation types (manipulation, bias, AI-generated content, out-of-context) from six social platforms. The authors propose FakeAgent, a multi-agent reasoning framework combining neural networks and large language models, which achieves… Zeng et al. · ACM International Conference · 2026

Deepfakes & multimodalDetection methods Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language ModelsThis paper introduces DECEPTIONDECODED, a benchmark of 12,000 image-caption pairs for evaluating multimodal misinformation detection with focus on creator intent. The authors find that state-of-the-art vision-language models struggle with intent reasoning and rely on superficial cues, motivating a framework for intent-aware multimodal… Wu et al. · ICLR 2026 · 2026