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Paper List Available
Written on 16.04.2025 14:18 by Ziqing Yang
Dear all,
The paper list is online. Please select three papers (ranked by preference) and send them to Ziqing Yang (ziqing.yang@cispa.de) by 10 a.m. on 18.04.2025.
Note that the assignment will be based on the first-come, first-served principle.
The assignment will be informed at 2 pm on 21.04.2025.
Best,
Ziqing
Paper List
- HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate Campaigns
- Moderating New Waves of Online Hate with Chain-of-Thought Reasoning in Large Language Models
- Aunties, Strangers, and the FBI: Online Privacy Concerns and Experiences of Muslim-American Women
- "HOT" ChatGPT: The promise of ChatGPT in detecting and discriminating hateful, offensive, and toxic comments on social media
- TUBERAIDER: Attributing Coordinated Hate Attacks on YouTube Videos to their Source Communities
- TROLLMAGNIFIER: Detecting State-Sponsored Troll Accounts on Reddit
- "Dummy Grandpa, do you know anything?": Identifying and Characterizing Ad Hominem Fallacy Usage in the Wild
- You Know What I Meme: Enhancing People’s Understanding and Awareness of Hateful Memes Using Crowdsourced Explanations
- On the Evolution of (Hateful) Memes by Means of Multimodal Contrastive Learning
- Understanding and Detecting Hateful Content Using Contrastive Learning
- Moderating Illicit Online Image Promotion for Unsafe User-Generated Content Games Using Large Vision-Language Models
- DISARM: Detecting the Victims Targeted by Harmful Memes
- Machine-Made Media: Monitoring the Mobilization of Machine-Generated Articles on Misinformation and Mainstream News Websites
- DeepPhish: Understanding User Trust Towards Artificially Generated Profiles in Online Social Networks
- Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resources
- Understanding the Use of Images to Spread COVID-19 Misinformation on Twitter
- Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots
- Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
- Toxicity in ChatGPT: Analyzing Persona-Assigned Language Models
- A Holistic Approach to Undesired Content Detection in the Real World
- You Only Prompt Once: On the Capabilities of Prompt Learning on Large Language Models to Tackle Toxic Content
- From Meme to Threat: On the Hateful Meme Understanding and Induced Hateful Content Generation in Open-Source Vision Language Models
- On the proactive generation of unsafe images from text-to-image models using benign prompts
- SneakyPrompt: Jailbreaking Text-to-image Generative Models
- Unsafe Diffusion: On the Generation of Unsafe Images and Hateful Memes From Text-To-Image Models
- Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models
- RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural Prompts
- Explainable Fake News Detection with Large Language Model via Defense Among Competing Wisdom
- Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks
- Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions
- Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection
- Can LLM-Generated Misinformation Be Detected?
- Disinformation Detection: An Evolving Challenge in the Age of LLMs
- On the Risk of Misinformation Pollution with Large Language Models
- From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake News