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arXiv:2603.13356v1 Announce Type: new Abstract: Standard approaches to Robust Reinforcement Learning assume that feedback sources are either globally trustworthy or globally adversarial. In this paper, …
arXiv:2603.13816v1 Announce Type: new Abstract: Hospital logistics management faces growing pressure from internal operations and external emergencies, with artificial intelligence (AI) holding untapped potential to …
arXiv:2603.13676v1 Announce Type: new Abstract: PET theranostics is transforming precision oncology, yet treatment response varies substantially; many patients receiving 177Lu-PSMA radioligand therapy (RLT) for metastatic …
arXiv:2603.13266v1 Announce Type: new Abstract: As large language models (LLMs) continue to grow in size, their abilities to tackle complex tasks have significantly improved. However, …
arXiv:2603.13818v1 Announce Type: new Abstract: Precipitation nowcasting is vital for flood warning, agricultural management, and emergency response, yet two bottlenecks persist: the prohibitive cost of …
arXiv:2603.13246v1 Announce Type: new Abstract: This paper proposes a Hadith-inspired multi-axis trust modeling framework, motivated by a structurally analogous problem in classical Hadith scholarship: assessing …
arXiv:2603.13348v1 Announce Type: new Abstract: Tool use represents a critical capability for AI agents, with recent advances focusing on leveraging reinforcement learning (RL) to scale …
arXiv:2603.13261v1 Announce Type: new Abstract: Electroencephalography (EEG) classification plays a key role in brain-computer interface (BCI) systems, yet it remains challenging due to the low …
arXiv:2603.13331v1 Announce Type: new Abstract: Grokking is the sudden generalization that appears long after a model has perfectly memorized its training data. Although this phenomenon …
arXiv:2603.13655v1 Announce Type: new Abstract: The recent escalation of the Iran Israel USA conflict in 2026 has triggered widespread global discussions across social media platforms. …
arXiv:2603.13251v1 Announce Type: new Abstract: Traditional benchmarks like HumanEval and MBPP test logic and syntax effectively, but fail when code must produce dynamic, pedagogical visuals. …
arXiv:2603.13612v1 Announce Type: new Abstract: Routing a query through an appropriate LLM is challenging, particularly when user preferences are expressed in natural language and model …