SSLogic uses LLM agents in a closed Generate-Validate-Refine loop to evolve 953 logic task families from 400 seeds, producing data that yields benchmark gains of +5.2 on SynLogic, +3.0 on AIME25, and +5.5 on BBH.
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Scaling the Scaling Logic: Agentic Meta-Synthesis of Logic Reasoning
SSLogic uses LLM agents in a closed Generate-Validate-Refine loop to evolve 953 logic task families from 400 seeds, producing data that yields benchmark gains of +5.2 on SynLogic, +3.0 on AIME25, and +5.5 on BBH.