Misinformation
277 papers with code • 1 benchmarks • 38 datasets
Benchmarks
These leaderboards are used to track progress in Misinformation
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Datasets
Hateful Memes
LIAR
DFDC
Hateful Memes Challenge
FakeNewsNet
MEIR
Latest papers
Misinformation Resilient Search Rankings with Webgraph-based Interventions
casos-ideas-cmu/misinformation-resilient-search-rankings
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The proliferation of unreliable news domains on the internet has had wide-reaching negative impacts on society.
A (More) Realistic Evaluation Setup for Generalisation of Community Models on Malicious Content Detection
rahelbeloch/meta-learning-gnns
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This mismatch can be partially attributed to the limitations of current evaluation setups that neglect the rapid evolution of online content and the underlying social graph.
DiffusionFace: Towards a Comprehensive Dataset for Diffusion-Based Face Forgery Analysis
The rapid progress in deep learning has given rise to hyper-realistic facial forgery methods, leading to concerns related to misinformation and security risks.
MMIDR: Teaching Large Language Model to Interpret Multimodal Misinformation via Knowledge Distillation
Automatic detection of multimodal misinformation has gained a widespread attention recently.
Ax-to-Grind Urdu: Benchmark Dataset for Urdu Fake News Detection
In this paper, we curate and contribute the first largest publicly available dataset for Urdu FND, Ax-to-Grind Urdu, to bridge the identified gaps and limitations of existing Urdu datasets in the literature.
Unveiling the Truth: Exploring Human Gaze Patterns in Fake Images
Creating high-quality and realistic images is now possible thanks to the impressive advancements in image generation.
ConspEmoLLM: Conspiracy Theory Detection Using an Emotion-Based Large Language Model
Driven by a comprehensive analysis of conspiracy text that reveals its distinctive affective features, we propose ConspEmoLLM, the first open-source LLM that integrates affective information and is able to perform diverse tasks relating to conspiracy theories.
Cross-Lingual Learning vs. Low-Resource Fine-Tuning: A Case Study with Fact-Checking in Turkish
While misinformation is prevalent in other languages, the majority of research in this field has concentrated on the English language.
Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource Limitations
dogregor/pretrain_gnns_fakenewsnet
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Pre-training of neural networks has recently revolutionized the field of Natural Language Processing (NLP) and has before demonstrated its effectiveness in computer vision.
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models
Large language models generate high-quality responses with potential misinformation, underscoring the need for regulation by distinguishing AI-generated and human-written texts.
