2 papers
cs.CL2026
Read as You See: Guiding Unimodal LLMs for Low-Resource Explainable Harmful Meme Detection
Fengjun Pan, Xiaobao Wu, Tho Quan +1
Detecting harmful memes is crucial for safeguarding the integrity and harmony of online environments, yet existing detection methods are often resource-intensive, inflexible, and l…
cs.CL2024
Are LLMs Good Zero-Shot Fallacy Classifiers?
Fengjun Pan, Xiaobao Wu, Zongrui Li +1
Fallacies are defective arguments with faulty reasoning. Detecting and classifying them is a crucial NLP task to prevent misinformation, manipulative claims, and biased decisions.…