Standard LLMs make frequent errors on small graph coloring problems, while reasoning models o1-mini and DeepSeek-R1 make fewer but still nonzero errors, and no model reaches perfect accuracy.
Kimi k1.5 : Scaling reinforcement learning with LLMs , 2025
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Evaluating the Systematic Reasoning Abilities of Large Language Models through Graph Coloring
Standard LLMs make frequent errors on small graph coloring problems, while reasoning models o1-mini and DeepSeek-R1 make fewer but still nonzero errors, and no model reaches perfect accuracy.