Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces 事件

Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces arXiv:2606.05464v1 Announce Type: new Abstract: Verifiable reward training has improved mathematical and coding reasoning, but these domains capture only part of step-by-step decision making. Many real-world tasks require finding a high-value feasible plan among many valid alternatives. We introduce OPT*, a scalable family of optimization-style tasks for training and evaluating LLM step-by-step optimization-like reaso