Papers with AI detection

3 papers
Automatic Authorship Analysis in Human-AI Collaborative Writing (2024.lrec-main)

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Challenge: Existing methods for authorship analysis and text detection are limited . authors: human-AI collaborative writing poses a potential challenge for existing methods .
Approach: They investigate the extent to which existing AI detection and authorship analysis models can perform classification on data generated in human-AI collaborative writing sessions.
Outcome: The proposed models outperform existing models on human-AI collaborative writing data . authors say human- AI co-written text will require adapting models in the near future .
Catch Me If You Can? Not Yet: LLMs Still Struggle to Imitate the Implicit Writing Styles of Everyday Authors (2025.findings-emnlp)

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Challenge: Personal style is often subtle and implicit, making it difficult to specify through prompts yet essential for user-aligned generation.
Approach: They evaluate LLMs' ability to imitate personal writing styles via in-context learning from user-authored samples.
Outcome: The proposed model can imitate personal writing styles from a small number of user-authored samples.
PunMemeCN: A Benchmark to Explore Vision-Language Models’ Understanding of Chinese Pun Memes (2025.emnlp-main)

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Challenge: Pun memes combine wordplay with visual elements to create humor, irony, or other rhetorical effects.
Approach: They propose a benchmark to assess Chinese pun memes' processing capabilities across three progressive tasks: pun meme detection, sentiment analysis, and chat-driven meme response.
Outcome: The proposed model can detect pun memes, analyze sentiments, and respond to chats, while ignoring homophone wordplay.

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