A Six-Dimensional Taxonomy of Post-Training Adaptation Techniques with Applications in AI Governance
Post-training adaptation has become central to modern machine learning practice and includes techniques such as retraining, fine-tuning, parameter-efficient adaptation, alignment, retrieval augmentation, model editing, unlearning, calibration, and Multimodal Instruction Tuning. However, the literature remains fragmented across technique families, model classes, and deployment contexts, making it difficult to compare methods or describe how a trained model has been modified. This survey synthesiz
Record details
Published: 6 August 2026
Source: arXiv cs.LG
Category: Research
Topics: Regulation · Safety & alignment
Retrieved: 7 August 2026
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How to cite this record
ethics.ai (6 August 2026), “A Six-Dimensional Taxonomy of Post-Training Adaptation Techniques with Applications in AI Governance,” evidence record 17391, https://ethics.ai/record/17391 (originally published by arXiv cs.LG).
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