LLMLow
Out of Tune: Fine-Tuning Foundation Models Leads to Unpredictable Safety Drift
- Occurred
- Apr 30, 2026
- Published
- Apr 30, 2026
- Source
- Center for Democracy and Technology
Summary
In addition to CDT, this report was authored by Emaan Bilal and Dylan Hadfield-Menell of the Algorithmic Alignment Group at the Massachusetts Institute of Technology (MIT). [ PDF version] General-purpose AI models are increasingly adapted by downstream developers for specialized uses — from medical transcription to legal contract analysis. This raises critical governance questions related to […] The post Out of Tune: Fine-Tuning Foundation Models Leads to Unpredictable Safety Drift appeared first on Center for Democracy and Technology.
Classification
Category confidence: 90%
Severity confidence: 95%
Rationale: Research paper discussing safety drift in fine-tuned foundation models without concrete incident.
Classifier: Qwen/Qwen3.5-35B-A3B-FP8