The rStar2-Agent framework boosts a 14B model to outperform a 671B giant, offering a path to state-of-the-art AI without ...

Abstract: We study the data-driven finite-horizon linear quadratic regularization (LQR) problem reformulated as a semidefinite program (SDP). Our contribution is to propose two novel accelerated first ...

Abstract: Pretrained Foundation Models (PFMs) are regarded as a promising accelerator for the development of various Artificial Intelligence (AI) applications, and have recently been widely fine-tuned ...