Yang Tang

Event-triggered control can maintain performance levels of time-triggered systems while effectively managing computational delays in networked environments.

Delayed feedback in reinforcement learning can be effectively managed by modeling discrepancies with diffusion techniques, leading to improved policy performance in challenging environments.

LazyMCoT achieves training-free visual grounding that rivals traditional methods while cutting inference time, redefining efficiency in multimodal reasoning.

Projector Drift reveals a hidden vulnerability in omni-modal systems that can significantly impair audio retrieval, but a simple fine-tuning strategy can effectively address it.

Foundation models are poised to revolutionize multi-agent systems by enabling semantic-level reasoning and flexible coordination that surpasses the limitations of classical approaches.

Unlock the power of MLLMs for structured data like human skeletons with a differentiable rendering approach that allows end-to-end training.