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Paper list of misinformation research using (multi-modal) large language models, i.e., (M)LLMs.
| Date | Stars |
|---|---|
| 2026-07-31 | 333 |
| 2026-08-02 | 333 |
| 2026-08-06 | 333 |
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# LLM-for-misinformation-research A curated paper list of misinformation research using (multi-modal) large language models, i.e., (M)LLMs. ## Methods for Detection and Verification ### As an Information/Feature Provider, Data Generator, and Analyzer > An LLM can be seen as a (sometimes not reliable) knowledge provider, an experienced expert in specific areas, and a relatively cheap data generator (compared with collecting from the real world). For example, LLMs could be a good analyzer of social commonsense/conventions. - **Cheap-fake Detection with LLM using Prompt Engineering**[[paper]](https://arxiv.org/abs/2306.02776)   - **Faking Fake News for Real Fake News Detection: Propaganda-Loaded Training Data Generation**[[paper]](https://doi.org/10.18653/v1/2023.acl-long.815)   - **Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection**[[paper]](https://ojs.aaai.org/index.php/AAAI/article/view/30214)   - **Analysis of Disinformation and Fake News Detection Using Fine-Tuned Large Language Model**[[paper]](https://arxiv.org/abs/2309.04704)   - **Detecting Misinformation with LLM-Predicted Credibility Signals and Weak Supervision**[[paper]](https://arxiv.org/abs/2309.07601)   - **FakeGPT: Fake News Generation, Explanation and Detection of Large Language Model**[[paper]](https://arxiv.org/abs/2310.05046)   - **Fighting Fire with Fire: The Dual Role of LLMs in Crafting and Detecting Elusive Disinformation**[[paper]](https://aclanthology.org/2023.emnlp-main.883/)   - **Language Models Hallucinate, but May Excel at Fact Verification**[[paper]](https://arxiv.org/abs/2310.14564)   - **Clean-label Poisoning Attack against Fake News Detection Models**[[paper]](https://doi.org/10.1109/BigData59044.2023.10386777)   - **Rumor Detection on Social Media with Crowd Intelligence and ChatGPT-Assisted Networks**[[paper]](https://doi.org/10.18653/v1/2023.emnlp-main.347)   - **LLMs are Superior Feedback Providers: Bootstrapping Reasoning for Lie Detection with Self-Generated Feedback**[[paper]](https://tanushreebanerjee.github.io/pdfs/diplomacy_main.pdf)  - **Can Large Language Models Detect Rumors on Social Media?**[[paper]](https://arxiv.org/abs/2402.03916)   - **TELLER: A Trustworthy Framework for Explainable, Generalizable and Controllable Fake News Detection**[[paper]](https://arxiv.org/abs/2402.07776)   - **DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection**[[paper]](https://arxiv.org/abs/2402.10426)   - **Enhancing large language model capabilities for rumor detection with Knowledge-Powered Prompting**[[paper]](https://doi.org/10.1016/j.engappai.2024.108259) ![](https://img.sh
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e129e3280185a90b, topic:large-language-models