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Princeton faculty voted to require proctoring for in-person exams, ending a 133-year-old honor system tradition, citing the rise of AI and personal electronic devices as major factors in increased cheating.
This paper introduces MELD, a detector for AI-generated text that uses multi-task learning with auxiliary heads for generator family, attack type, and source domain to improve robustness. MELD achieves strong performance on the RAID benchmark and maintains low false-positive rates under adversarial attacks.
LLMSniffer is a detection framework that fine-tunes GraphCodeBERT with supervised contrastive learning to distinguish AI-generated code from human-written code, achieving 78% accuracy on GPTSniffer and 94.65% on Whodunit benchmarks. The approach addresses critical challenges in academic integrity and code quality assurance by combining code-structure-aware embeddings with contrastive learning and comment removal preprocessing.
OpenAI publishes a guide for students on using ChatGPT responsibly to enhance writing and thinking skills while maintaining academic integrity, emphasizing transparency and proper citation of AI usage.