SinoXivAs Large Language Models (LLMs) are increasingly deployed in autonomous, high-stakes environments, the fragility of current Reinforcement Learning from Human Feedback (RLHF) alignment protocols remain...
Dynamic data distributions, system failures, and low-latency, cost-effective processing are becoming more of a challenge to modern real-time data pipelines. Current streaming architectures are based o...
The current data validation systems are mostly reactive, static, and resource-heavy which may lead to interruptions of pipelines and will not be able to detect data corruption in real-time settings. T...
Healthcare revenue cycle management (RCM) loses billions annually to claim denials, yet existing machine learning approaches treat billing as a prediction problem rather than a decision problemthey pr...
Diffusion policies have emerged as a powerful approach for robotic control, demonstrating superior expressiveness in modeling multimodal action distributions compared to conventional policy networks. ...
Traditional approaches to anticancer dosing typically rely on fixed protocols that often overlook how patients respond differently to treatment. This can limit both effectiveness and safety. In this w...
