Jiacheng Cui

AutoDesign outperforms existing design systems by aligning with human design principles and achieving superior poster generation quality through recursive self-improvement.

A simple training framework boosts pixel-level tampering detection performance in VLMs by over 26%, showcasing the power of balanced sampling and late-injection strategies.

Mixed-authorship documents can be harder to detect than purely human or AI-generated texts, challenging existing assumptions about AI-text detection.

Uncover a model's "digital DNA" – its pretraining data mixture – from its outputs alone, even without access to the training data.

Token compression in diffusion models no longer has to sacrifice classification accuracy for faster generation – BiGain boosts both.