4 accepted papers
Federated fine-tuning is critical for improving the performance of large language models (LLMs) in handling domain-specific tasks while keeping training data decentralized and private. However, prior work has shown that clients' private data can actually be recovered via gradient inversion attacks.…
While self-consistency methods have emerged as a promising approach to enhance the correctness of large language model (LLM) outputs by aggregating multiple stochastic samples, they suffer from two critical limitations, resulting in high computation cost. First, they evaluate output consistency mono…
Robot-assisted vascular interventional surgery can isolate interventionists and X-ray radiation, and improve surgical accuracy. However, the leader side outside the operating room still has problems such as incomplete collection of operating information and unrealistic tactile feedback. The main obj…
Research on endovascular surgery robots (ESR) is continuously developing, because ESR can protect surgeons from radiation exposure. For designing an ESR manipulator, the main challenge is controlling the soft surgical tools and measuring the endovascular stress simultaneously. In this letter, a flex