AGPO applies asymmetric negative-dominant reinforcement and variance-scaled group advantages in RLVR to preserve base model exploration while boosting accuracy and pass@k on math benchmarks and industrial ad relevance data.
One way to do this is to consider the parity (odd or even) of the numbers
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AGPO: Asymmetric Group Policy Optimization for Verifiable Reasoning and Search Ads Relevance at JD
AGPO applies asymmetric negative-dominant reinforcement and variance-scaled group advantages in RLVR to preserve base model exploration while boosting accuracy and pass@k on math benchmarks and industrial ad relevance data.