risk-aware-ai

This paper proposes consequence-aware test-time compute allocation, routing higher-stakes software engineering tasks to larger compute budgets based on predicted failure cost rather than just difficulty. Evaluated on SWE-bench Lite and Multi-SWE-bench mini, the approach reduces cost-weighted loss by 22–33% compared to difficulty-aware routing.