⚡ AI-Lesson Articles

In honor of Apple’s 50th anniversary, we picked 50 of our favorite Apple products, from the OG iPhone to GarageBand. Now we’re ranking them as a community, and

Apple turns 50 next week, and we're going to spend the week covering the company, its products, its legacy, and its future. But mostly, we're going to spend the

arXiv:2603.24621v1 Announce Type: new Abstract: We introduce ARC-AGI-3, an interactive benchmark for studying agentic intelligence through novel, abstract, turn

arXiv:2603.24676v1 Announce Type: new Abstract: Multi-agent systems powered by large language models (LLMs) are increasingly deployed in settings that shape con

arXiv:2603.24736v1 Announce Type: new Abstract: In the design and safety analysis of advanced reactor systems, constructing input files for system-level thermal

arXiv:2603.24742v1 Announce Type: new Abstract: AI safety is an increasingly urgent concern as the capabilities and adoption of AI systems grow. Existing evolut

arXiv:2603.24747v1 Announce Type: new Abstract: The emergence of large language model agents capable of invoking external tools has created urgent need for form

arXiv:2603.24768v1 Announce Type: new Abstract: The engineering design research community has studied agentic AI systems that use Large Language Model (LLM) age

arXiv:2603.24787v1 Announce Type: new Abstract: Routing has emerged as a promising strategy for balancing performance and cost in large language model (LLM) sys

arXiv:2603.24853v1 Announce Type: new Abstract: Ethical debates in AI have primarily focused on back-end issues such as data governance, model training, and alg

arXiv:2603.24856v1 Announce Type: new Abstract: Emergency response systems generate data from many agencies and systems. In practice, correlating and updating t

arXiv:2603.24866v1 Announce Type: new Abstract: The physical world is not merely visual; it is governed by rigorous structural and procedural constraints. Yet,

arXiv:2603.24904v1 Announce Type: new Abstract: We prove that platform-deterministic inference is necessary and sufficient for trustworthy AI. We formalize this

arXiv:2603.24929v1 Announce Type: new Abstract: Understanding and quantifying uncertainty in large language model (LLM) outputs is critical for reliable deploym

arXiv:2603.24933v1 Announce Type: new Abstract: The growing prominence of cryptocurrencies has triggered widespread public engagement and increased speculative

arXiv:2603.24943v1 Announce Type: new Abstract: This paper introduces \textbf{FinMCP-Bench}, a novel benchmark for evaluating large language models (LLMs) in so

arXiv:2603.24947v1 Announce Type: new Abstract: This paper provides some of the first large-scale descriptive evidence on how consumers adopt and use platform-e

arXiv:2603.24961v1 Announce Type: new Abstract: Assessing student handwritten scratchwork is crucial for personalized educational feedback but presents unique c

arXiv:2603.24963v1 Announce Type: new Abstract: Modern computational advertising platforms typically rely on recommendation systems to predict user responses, s

arXiv:2603.24967v1 Announce Type: new Abstract: Understanding why a large language model (LLM) is uncertain about the response is important for their reliable d

arXiv:2603.25001v1 Announce Type: new Abstract: Failure attribution is essential for diagnosing and improving multi-agent systems (MAS), yet existing benchmarks

arXiv:2603.25022v1 Announce Type: new Abstract: Knowledge distillation, model extraction, and behavior transfer have become central concerns in frontier AI. The

arXiv:2603.25025v1 Announce Type: new Abstract: Autoregressive neural PDE simulators predict the evolution of physical fields one step at a time from a finite h

arXiv:2603.25031v1 Announce Type: new Abstract: In psychological support and emotional companionship scenarios, the core limitation of large language models (LL