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cs.AI2026
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +306
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
cs.AI2026
Agentic Risk-Aware Set-Based Engineering Design
Varun Kumar, George Em Karniadakis
This paper introduces a multi-agent framework guided by Large Language Models (LLMs) to assist in the early stages of engineering design, a phase often characterized by vast parame…
cs.AI2026
AgenticSciML: Collaborative Multi-Agent Systems for Emergent Discovery in Scientific Machine Learning
Qile Jiang, George Karniadakis
Scientific Machine Learning (SciML) integrates data-driven inference with physical modeling to solve complex problems in science and engineering. However, the design of SciML archi…