Task-CoEvolve: Efficient Agent Harness Optimization via Adaptive Task Selection
tokenbender · x · 2026-08-22
The paper 'Task-CoEvolve' proposes a method to efficiently optimize LLM Agent Harnesses via adaptive validation task selection.
Key Mechanism:
- Problem: Traditional methods evaluate the full fixed validation set every iteration, which is costly.
- Innovation: Focuses only on the 20% of tasks where model candidates disagree.
- Effect: Uses variance-weighted sampling to focus on tasks at the agent's capability frontier, driving the harness to optima faster and cheaper.
- Experiments: Shows superior performance over fixed sets on Terminal-Bench 2.1.
Related event: Task-CoEvolve Algorithm Cuts Evaluation Costs by 80%(2 posts)→
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