OptSkills: Learning Generalizable Optimization Skills from Problem Archetypes via Cluster-Based Distillation
cs.AI, cs.LG
Submitted: 2026-05-28
Updated: 2026-09-02
Code: https://github.com/fujiwaranoM0kou/OptSkills
Terminology
Sources
- EvoSkill: Automated Skill Discovery for Multi-Agent Systems
- DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
- XSkill: Continual Learning from Experience and Skills in Multimodal Agents
- Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization
- AlphaOPT: Formulating Optimization Programs with Self-Improving LLM Experience Library
- Large-Scale Optimization Model Auto-Formulation: Harnessing LLM Flexibility via Structured Workflow
- AutoOR: Scalably Post-training LLMs to Autoformalize Operations Research Problems
- Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills
- MIRROR: A Multi-Agent Framework with Iterative Adaptive Revision and Hierarchical Retrieval for Optimization Modeling in Operations Research
- Qwen3 Technical Report
- ORThought: Benchmarking and Automating Logistics Optimization Modeling
- AutoSkill: Experience-Driven Lifelong Learning via Skill Self-Evolution
- MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agents
- Memento-Skills: Let Agents Design Agents
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