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FlowBalance introduces a verifier-grounded self-improvement technique that improves math reasoning performance by an average of 2.12 over GRPO on the Qwen3-8B model, offering faster training, enhanced stability, and greater solution diversity.
FlowBalance is a verifier-grounded self-improvement method that calibrates on-policy reasoning experience to enhance AI model performance and stability in mathematical reasoning tasks.
Introduces SBCO, a self-supervised verifier-grounded harness optimizer for planning agents that improves agent outputs via approximate block coordinate ascent, matching or exceeding self-modifying baselines with far less compute.