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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

  1. HateBench: Benchmarking Hate Speech Detectors on LLM-Generated Content and Hate Campaigns
  2. Moderating New Waves of Online Hate with Chain-of-Thought Reasoning in Large Language Models
  3. Aunties, Strangers, and the FBI: Online Privacy Concerns and Experiences of Muslim-American Women
  4. "HOT" ChatGPT: The promise of ChatGPT in detecting and discriminating hateful, offensive, and toxic comments on social media
  5. TUBERAIDER: Attributing Coordinated Hate Attacks on YouTube Videos to their Source Communities
  6. TROLLMAGNIFIER: Detecting State-Sponsored Troll Accounts on Reddit
  7. "Dummy Grandpa, do you know anything?": Identifying and Characterizing Ad Hominem Fallacy Usage in the Wild
  8. You Know What I Meme: Enhancing People’s Understanding and Awareness of Hateful Memes Using Crowdsourced Explanations
  9. On the Evolution of (Hateful) Memes by Means of Multimodal Contrastive Learning
  10. Understanding and Detecting Hateful Content Using Contrastive Learning
  11. Moderating Illicit Online Image Promotion for Unsafe User-Generated Content Games Using Large Vision-Language Models
  12. DISARM: Detecting the Victims Targeted by Harmful Memes
  13. Machine-Made Media: Monitoring the Mobilization of Machine-Generated Articles on Misinformation and Mainstream News Websites
  14. DeepPhish: Understanding User Trust Towards Artificially Generated Profiles in Online Social Networks
  15. Open-Domain, Content-based, Multi-modal Fact-checking of Out-of-Context Images via Online Resources
  16. Understanding the Use of Images to Spread COVID-19 Misinformation on Twitter
  17. Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots
  18. Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
  19. Toxicity in ChatGPT: Analyzing Persona-Assigned Language Models
  20. A Holistic Approach to Undesired Content Detection in the Real World
  21. You Only Prompt Once: On the Capabilities of Prompt Learning on Large Language Models to Tackle Toxic Content
  22. From Meme to Threat: On the Hateful Meme Understanding and Induced Hateful Content Generation in Open-Source Vision Language Models
  23. On the proactive generation of unsafe images from text-to-image models using benign prompts
  24. SneakyPrompt: Jailbreaking Text-to-image Generative Models
  25. Unsafe Diffusion: On the Generation of Unsafe Images and Hateful Memes From Text-To-Image Models
  26. Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models
  27. RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural Prompts
  28. Explainable Fake News Detection with Large Language Model via Defense Among Competing Wisdom
  29. Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks
  30. Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions
  31. Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection
  32. Can LLM-Generated Misinformation Be Detected?
  33. Disinformation Detection:  An Evolving Challenge in the Age of LLMs
  34. On the Risk of Misinformation Pollution with Large Language Models
  35. From Skepticism to Acceptance: Simulating the Attitude Dynamics Toward Fake News
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