Researchers submitted a system to SemEval-2026 Task 9 for detecting multilingual online polarization using transformer-based models with class weighting and threshold tuning. Their approach achieved c…
Researchers at arXiv found that using large language models (LLMs) like GPT-5.2 to label training data for entity matching can reduce manual labeling effort by hundreds of hours, with student models p…
A user submitted a fake AI-generated article to Hacker News, which was flagged after detection. Testing local AI detectors on a 2013 Paul Graham essay showed it was rated as more likely AI-generated t…
Researchers introduced HierBias, a hierarchical context-conditioned media bias detector that models document context to improve sentence-level bias classification. The system achieved 0.853 F1 and 0.7…
A paper by Saha et al. (arXiv 2506.07001) demonstrates that detector-guided paraphrasing using RoBERTa as a reward reduces the true positive rate of AI-generated text detectors by 87.88% across Binocu…
Researchers at the University of Washington and Allen Institute for AI conducted the first fine-grained study of narrative features in Dolma, a 3-trillion-token open LLM pretraining corpus. They devel…
Fine-tuned RoBERTa achieved a 0.62 macro-F1 score for classifying misinformation responses on Reddit, outperforming the best zero-shot large language model (Claude Haiku 4.5) at 0.50 while costing a f…
Personal analogy comparing career phases to three types of large language model (LLM) architectures. The author describes their early education as an "encoder-only" phase focused on absorbing knowledg…