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arXiv:2603.00285v1 Announce Type: new Abstract: Evaluating AI agents in finance faces two key challenges: static benchmarks require costly expert annotation yet miss the dynamic decision-making …
arXiv:2603.00309v1 Announce Type: new Abstract: The increasingly popular agentic AI paradigm promises to harness the power of multiple, general-purpose large language model (LLM) agents to …
arXiv:2603.00349v1 Announce Type: new Abstract: Real-world scenarios increasingly require multiple embodied agents to collaborate in dynamic environments under embodied constraints, as many tasks exceed the …
arXiv:2603.00350v1 Announce Type: new Abstract: The prevailing paradigm in artificial intelligence research equates progress with scale: larger models trained on broader datasets are presumed to …
arXiv:2603.00374v1 Announce Type: new Abstract: Offline learning of strategies takes data efficiency to its extreme by restricting algorithms to a fixed dataset of state-action trajectories. …
arXiv:2603.00376v1 Announce Type: new Abstract: \textit{NeuroHex} is a hexagonal coordinate system designed to support highly efficient world models and reference frames for online adaptive AI …
arXiv:2603.00451v1 Announce Type: new Abstract: Accurate and unambiguous guidelines are critical for large language model (LLM) based graders, yet manually crafting these prompts is often …
arXiv:2603.00460v1 Announce Type: new Abstract: Clinical decision-making requires synthesizing heterogeneous evidence, including patient histories, clinical guidelines, and trajectories of comparable cases. While large language models …
arXiv:2603.00465v1 Announce Type: new Abstract: Automated assessment of open-ended student responses is a critical capability for scaling personalized feedback in education. While large language models …
arXiv:2603.00469v1 Announce Type: new Abstract: Operators of Earth observation satellites need justifications for scheduling decisions: why a request was selected, rejected, or what changes would …
arXiv:2603.00472v1 Announce Type: new Abstract: Agentic AI systems exhibit numerous crosscutting concerns -- security, observability, cost management, fault tolerance -- that are poorly modularized in …
arXiv:2603.00490v1 Announce Type: new Abstract: The rapid progress of Multimodal Large Language Models (MLLMs) marks a significant step toward artificial general intelligence, offering great potential …