Junming Zhang

Intern-S2-Preview-397B not only excels in multimodal scientific reasoning but also enhances biological instruction performance without altering its foundational architecture.

CAZO achieves state-of-the-art test-time adaptation performance while slashing memory requirements, making it a game-changer for on-device AI applications.

Independently scaling long-term memory in language models can yield better performance with fewer parameters than simply increasing model size.