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arXiv:2603.05560v1 Announce Type: cross Abstract: We investigate the Continuous-Time Koopman Autoencoder (CT-KAE) as a lightweight surrogate model for long-horizon ocean state forecasting in a two-layer …
arXiv:2603.05607v1 Announce Type: cross Abstract: Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by small annotated datasets …
arXiv:2603.05532v1 Announce Type: cross Abstract: Despite continuing hype about the role of AI in drug discovery, no "AI-discovered drugs" have so far received regulatory approval. …
arXiv:2603.03668v1 Announce Type: cross Abstract: Solving constraints involving inductive (aka recursive) definitions is challenging. State-of-the-art SMT/CHC solvers and first-order logic provers provide only limited support …
arXiv:2603.06565v1 Announce Type: new Abstract: Deep reinforcement learning agents are often misaligned, as they over-exploit early reward signals. Recently, several symbolic approaches have addressed these …
arXiv:2603.05562v1 Announce Type: cross Abstract: We consider the problem of modifying a description logic concept in light of models represented as pointed interpretations. We call …
arXiv:2603.05514v1 Announce Type: cross Abstract: Systematic Literature Reviews (SLRs) are fundamental to scientific progress, yet the process is hindered by a fragmented tool ecosystem that …
arXiv:2603.05569v1 Announce Type: cross Abstract: Extracting insights from Electronic Health Record (EHR) databases often requires SQL expertise, creating a barrier for healthcare decision-making and research. …
arXiv:2603.05539v1 Announce Type: cross Abstract: We introduce VDCook: a self-evolving video data operating system, a configurable video data construction platform for researchers and vertical domain …
arXiv:2603.05578v1 Announce Type: cross Abstract: Research on self-evolving language agents has accelerated, drawing increasing attention to their ability to create, adapt, and maintain tools from …
arXiv:2603.05622v1 Announce Type: cross Abstract: High-Content Screening routinely generates massive volumes of cell painting images for phenotypic profiling. However, technical variations across experimental executions inevitably …
arXiv:2603.05553v1 Announce Type: cross Abstract: Function-calling agents -- large language models that invoke tools and APIs -- require high-quality, domain-specific training data spanning executable environments, …