OptSkills: Learning Generalizable Optimization Skills from Problem Archetypes via Cluster-Based Distillation 事件

OptSkills: Learning Generalizable Optimization Skills from Problem Archetypes via Cluster-Based Distillation arXiv:2605.29829v1 Announce Type: new Abstract: Leveraging Large Language Models (LLMs) to automatically formulate and solve optimization problems from natural language has emerged as an efficient paradigm for automated optimization. However, existing methods still exhibit limited generalization: they are sensitive to superficial narrative variations, reuse experience mainly at the case