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Opera is a verbal critic framework for long-horizon coding agents that treats each correction as a persistent note, tracking agent actions to distinguish mere compliance from actual resolution. It improves resolver rates by up to 15 percentage points across benchmarks and provides on-policy training data that boosts Qwen3.5-9B's SWE-Bench Pro performance without needing a critic at inference time.
Introduces Critic Experience Bank (CEB), a self-evolving critic framework for step-level confidence estimation in LLM agents that leverages a memory bank of past judgments and consequences to improve calibration without training.