Evaluation-Conditioned Training: Teaching Models to Generalize to Stronger Oversight Regimes

Feedback signals used to train Large Language Models (LLMs) are the primary driver of their behavior and our main lever for instilling alignment with human values and objectives. However, a key limitation of current post-training methods is the inability of human annotators and automated reward functions to faithfully capture the feedback we would like to give. We introduce Evaluation-Conditioned Training (ECT), a post-training framework that uses natural language to condition each training samp

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ethics.ai (10 August 2026), “Evaluation-Conditioned Training: Teaching Models to Generalize to Stronger Oversight Regimes,” evidence record 18440, https://ethics.ai/record/18440 (originally published by arXiv).

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