Learning to Optimize through Solver-Grounded Self-Play
Results indicate that with zero curated data, OPT-Zero matches state-of-the-art data-dependent methods while exhibiting substantially stronger generalizability, establishing self-play training as a highly scalable paradigm for advancing LLM reasoning in modeling and solving optimization problems.
Xia Jiang, Yao-Xin Wu, Chen-Yu Zhou et al.
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