Booth 21-25 | AI Data Management Zone | Tokyo Big Sight
Most AI text detectors look good in testing. They’re trained and evaluated on specific models, specific prompt styles, specific domains — and they perform well within that distribution. Then they
Before you reach for RLHF, before you design a reward model, before you start thinking about reinforcement learning from verifiable rewards — there’s a more fundamental question worth asking: has this model been properly fine-tuned on examples of the behavior you want? Supervised Fine-Tuning (SFT) sits between pre-training and the
