Rui Gan

The paper proposes a novel, locally deployable agentic workflow using large language models (LLMs) to accurately and privately detect various types of personally identifiable information (PII) within unstructured crash narratives.

LoopFM proposes a novel framework to significantly improve knowledge distillation for recommendation systems by structuring the rich intermediate embeddings of large foundation models as input features, thereby overcoming the limitations of single-scalar prediction transfer.

The paper proposes a pose-conditioned, permutation-equivariant denoiser to accurately reconstruct work zone geometry using noisy Ultra-Wideband (UWB) range data from connected and autonomous vehicles (CAVs).