Shi-Qi Yu

These findings support long-context inference in which pretrained models guide their own access to the information they retain, by introducing On-Demand Attention (ODA), a local-first decoding method that uses a lightweight recall head to selectively invoke global attention as its predicted benefit changes during generation.

Adapting foundation models with synthetic data can dramatically enhance face recognition accuracy, with some methods even surpassing traditional baselines.