Booth 21-25 | AI Data Management Zone | Tokyo Big Sight
There’s a quiet result from Cheng et al. (Renmin University and Microsoft Research, 2026) that I keep coming back to. They gave large language models access to a minimal sandbox
A new paper from Christopher Burger, Karmece Talley, and Christina Trotter (arXiv:2512.23587), accepted to the 59th Hawaii International Conference on System Sciences, asks a deceptively simple question: can today’s frontier LLMs reliably identify AI-generated text? They tested GPT-4, Claude, and Gemini in a computing-education setting, where the stakes — academic
