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This work introduces ExecCritic, combining a test--verify--revise scaffold with a role-specific reinforcement learning recipe for training agents within it, separating test construction from source-code repair.
On long-horizon complex search, TRACE substantially improves base-model tool-use ability using pure RL, without a cold-start supervised fine-tuning stage, an agentic mid-training stage, or training on live-web data.
Apodex 1.1 reaches the leading performance band despite using a substantially smaller model than many frontier systems, and the 35B-parameter Apodex 1.1 Mini further retains strong working capability in a locally deployable form.
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