acesearcher-reasoning-search-self-play

Train a single LLM to decompose complex queries into subquestions and integrate retrieved contexts through two-stage supervised and preference-based reinforcement fine-tuning, achieving 7.6% average improvement and matching 685B models with 32B parameters.

Independent GitHub snapshot · Automated classification · Original documentation governs