```markdown Root Node: Model Type |-- Open Source vs. Closed Source |-- Domain-specific vs. General |-- Multilingual vs. Monolingual |-- Vision-Language Models (VLMs) vs. Non-VLMs |-- Modular vs. Non-modular |-- Specialized vs. General-purpose |-- Embeddings-based vs. Non-Embeddings-based |-- Model Size (Small, Medium, Large, Extra-Large) |-- Additional Dimensions (as needed) |-- Model Architecture (e.g., Encoder-only, Decoder-only, Encoder-Decoder) |-- Training Methodology (e.g., Self-supervised, Supervised, Reinforcement Learning) |-- Data Source (e.g., Web-scale, Domain-specific, Synthetic) |-- Ethical Considerations (e.g., Bias, Fairness, Transparency) |-- Refine existing dimensions and categories based on new insights and feedback |-- Continuously update the taxonomy with new models and advancements in the field ```