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Anthropic researchers detail “model spec midtraining”, which adds a stage between pretraining and fine-tuning to improve generalization from alignment training

Model Spec Midtraining: Improving How Alignment Training Generalizes

alignment.anthropic.com

May 7, 2026

8 min read

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Summary

Model spec midtraining (MSM) trains models on synthetic documents about their Model Spec after pre-training and before alignment fine-tuning. MSM enhances generalization during alignment training and reduces agentic misalignment by influencing how models adopt values based on the Model Spec used.

Key Takeaways

Model spec midtraining (MSM) is a method designed to improve how models generalize from alignment fine-tuning by training them on synthetic documents that discuss their Model Spec.
MSM allows for control over the values a model learns from ambiguous demonstration data, enabling different models to generalize distinct values even when trained on the same dataset.
The application of MSM has been shown to reduce agentic misalignment and improve alignment in complex agentic settings after fine-tuning on simple conversation transcripts.
Training with MSM can lead to models that consistently prefer values aligned with their specified Model Spec in various domains, demonstrating its effectiveness in guiding model behavior.

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