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cs.AI2026
R-APS: Compositional Reasoning and In-Context Meta-Learning for Constrained Design via Reflective Adversarial Pareto Search
João Pedro Gandarela, Thiago Rios, Stefan Menzel +1
Large language models (LLMs) are fluent on open-ended tasks, yet in agentic settings, where a system must plan, use tools, and act over extended horizons, fluency does not ensure r…
cs.AI2026
Language Models Refine Mechanical Linkage Designs Through Symbolic Reflection and Modular Optimisation
João Pedro Gandarela, Thiago Rios, Stefan Menzel +1
Designing mechanical linkages involves combinatorial topology selection and continuous parameter fitting. We show that language models can systematically improve linkage designs th…