Hanzhe Hong

Audio and acceleration modalities can predict physical interactions with surprising accuracy, but the executor's architecture is the true bottleneck in achieving effective multimodal execution.

Traditional audits miss collusion entirely, allowing conspiracies to thrive under the guise of competitive pricing.

Prediction objectives shape the physical knowledge embedded in latent representations, revealing that some parameters are only captured under specific forecasting conditions.

Local names boost retrieval accuracy, but models still fail to generate images that faithfully represent specific street segments.