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Model Main Effects Fall Below 3% Across Three Agent Benchmarks, as DDR Recasts Leaderboards as a Deployment Reliability Problem
A new study uses generalizability theory to decompose results from TheAgentCompany, τ²-bench, and AppWorld, finding that agent–task interactions far outweigh average differences between agents. The authors propose the DDR reporting framework, which requires model-selection decisions to disclose task difficulty, holdout validation, cost, and required sample size.