Brian C. Keegan, Ph.D.

NEW: Fiction written by AI is easy to detect because it struggles with complex story structure, according to a new study. Researchers found that AI fiction has tells that go beyond the overuse of em-dashes and other obvious AI tropes and have more to do with the formulaic natu…

AI Fiction Is Easy to Detect Because It's Stupid and Bad, Research Finds 404media.co

Honglin Bao, Siyang Wu, Xiao Liu, Sida Li, Shiyun Cao, James A. Evans: Contemporary AI lacks the imagination to diverge or negate in science https://arxiv.org/abs/2606.08251 https://arxiv.org/pdf/2606.08251 https://arxiv.org/html/2606.08251

Contemporary AI lacks the imagination to diverge or negate in science arxiv.org

ACL 2026 was fun! We presented our benchmark, which reveals that frontier models struggle to moderate pluralistic communities on Reddit. A fun bonus: creating all the colorful plots for the paper! 🎨 Our paper, code, and benchmark are all available here: github.com/osome-iu/Plu...

GitHub - Zoher15/PluRule: PluRule: A multilingual, multimodal benchmark for detecting rule violations when moderating pluralistic communities on social media. github.com

Return of the solo author: The changing division of labor in science in the age of generative A https://arxiv.org/abs/2607.10780

Return of the solo author: The changing division of labor in science in the age of generative AI arxiv.org

The Reciprocal Impact of Science and Software: A Cross-Corpus Analysis of How Research Shapes Software and Software Enables Research https://arxiv.org/abs/2606.28120

The Reciprocal Impact of Science and Software: A Cross-Corpus Analysis of How Research Shapes Software and Software Enables Research arxiv.org

Dinesh Ayyappan, Carlos Castillo: Discriminatory Compliance: How LLMs Answer Queries from Protected Groups https://arxiv.org/abs/2606.21296 https://arxiv.org/pdf/2606.21296 https://arxiv.org/html/2606.21296

Discriminatory Compliance: How LLMs Answer Queries from Protected Groups arxiv.org

Dinesh Ayyappan, Carlos Castillo: Discriminatory Compliance: How LLMs Answer Queries from Protected Groups https://arxiv.org/abs/2606.21296 https://arxiv.org/pdf/2606.21296 https://arxiv.org/html/2606.21296

arxiv.org

Dinesh Ayyappan, Carlos Castillo: Discriminatory Compliance: How LLMs Answer Queries from Protected Groups https://arxiv.org/abs/2606.21296 https://arxiv.org/pdf/2606.21296 https://arxiv.org/html/2606.21296

Discriminatory Compliance: How LLMs Answer Queries from Protected Groups arxiv.org

Nina Brolich, Anna Neovesky: Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok https://arxiv.org/abs/2606.23300 https://arxiv.org/pdf/2606.23300 https://arxiv.org/html/2606.23300

Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok arxiv.org

Nina Brolich, Anna Neovesky: Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok https://arxiv.org/abs/2606.23300 https://arxiv.org/pdf/2606.23300 https://arxiv.org/html/2606.23300

arxiv.org

Nina Brolich, Anna Neovesky: Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok https://arxiv.org/abs/2606.23300 https://arxiv.org/pdf/2606.23300 https://arxiv.org/html/2606.23300

Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok arxiv.org