Cheng-Lin Wu

StrixAE achieves unprecedented audio enhancement performance by integrating a multimodal language model with a tailored reinforcement learning approach, setting a new benchmark in real-world audio restoration.

Co-Scientist not only accelerates scientific discovery but also ensures the reliability of generated research outputs, reducing hallucination and plagiarism in a double-blind study.

StepOPSD shows that focusing on individual agent steps, rather than entire trajectories, unlocks significant performance gains in multi-turn agent reinforcement learning.

As AI agents scale and interact, the Foundation Protocol offers a coordination layer that prioritizes accountability and governance, ensuring that the future of human-AI collaboration remains open and governable.