arXiv:2409.09451v5 Announce Type: replace-cross
Abstract: Foundation models pre-trained using self-supervised learning have shown powerful transfer learning capabilities on various downstream tasks, including language understanding, text generation, a…
arXiv:2604.18806v1 Announce Type: new
Abstract: 3D-IC netlist partitioning is commonly optimized using proxy objectives, while final PPA is treated as a costly evaluation rather than an optimization signal. This proxy-driven paradigm makes it difficul…
arXiv:2507.06321v2 Announce Type: replace-cross
Abstract: Collecting and annotating images for the purpose of training segmentation models is often cost prohibitive. In the domain of wildland fire science, this challenge is further compounded by the s…
arXiv:2604.18828v1 Announce Type: new
Abstract: Artificial Intelligence (AI) surrogate models provide a computationally efficient alternative to full-physics simulations, but no public datasets currently exist for training and validating models of hig…
arXiv:2604.19148v1 Announce Type: new
Abstract: Efficient and robust path planning hinges on combining all accessible information sources. In particular, the task of path planning for robotic environmental exploration and monitoring depends highly on …
arXiv:2604.18839v1 Announce Type: new
Abstract: Looped transformers scale computational depth without increasing parameter count by repeatedly applying a shared transformer block and can be used for iterative refinement, where each loop rewrites a ful…
arXiv:2604.18912v1 Announce Type: new
Abstract: Discovering optimal designs through sequential data collection is essential in many real-world applications. While Bayesian Optimization (BO) has achieved remarkable success in this setting, growing atte…
arXiv:2604.19522v1 Announce Type: new
Abstract: Bimanual mobile manipulation requires a seamless integration between high-level semantic reasoning and safe, compliant physical interaction – a challenge that end-to-end models approach opaquely and clas…
arXiv:2604.18936v1 Announce Type: new
Abstract: Despite the growing application of Large Language Models (LLMs) to theoretical physics, there is little academic exploration into how domain-specific physics reasoning ability develops while training the…
arXiv:2604.19536v1 Announce Type: new
Abstract: Recent navigation systems achieve strong benchmark results, yet real-world deployment often remains visibly stop-and-go. This bottleneck arises because the sense-inference-execution loop is still blockin…