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arXiv:2603.05525v1 Announce Type: cross Abstract: Deep learning, a subfield of machine learning, has gained importance in various application areas in recent years. Its growing popularity …
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, …
arXiv:2603.06394v1 Announce Type: new Abstract: Large language models (LLMs) can now translate a researcher's plain-language goal into executable computation, yet scientific workflows demand determinism, provenance, …
arXiv:2603.05565v1 Announce Type: cross Abstract: Generative AI compresses within-task skill differences while shifting economic value toward concentrated complementary assets, creating an apparent paradox: the technology …
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:2603.06565v1 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:2603.05623v1 Announce Type: cross Abstract: Camera-LiDAR fusion is widely used in autonomous driving to enable accurate 3D object detection. However, bird's-eye view (BEV) fusion detectors …
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:2603.05622v1 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:2603.06067v1 Announce Type: new Abstract: Formal argumentation is being used increasingly in artificial intelligence as an effective and understandable way to model potentially conflicting pieces …
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:2603.05542v1 Announce Type: cross Abstract: The rapid advancement of AI is transforming human-centered systems, with profound implications for human-AI interaction, human-data interaction, and visual analytics. …