Yiling Chen

Achieving precise timing control in audio-visual generation without model retraining could revolutionize how we synchronize speech and visuals in AI applications.

Achieving low regret in contextual procurement auctions reveals a nuanced tradeoff between welfare and incentive errors that could transform auction mechanisms.

Language models can bootstrap their reasoning abilities without human labels by learning from each other's aggregated answers, achieving significant gains in mathematical reasoning.

Unlock better flow field reconstructions: VSOPINN adaptively optimizes sensor placement within a PINN framework, boosting accuracy and robustness even with sparse or failing sensors.