A deep dive into exactly how text-only language models are finetuned to *see* images
The post How Vision Language Models Are Trained from “Scratch” appeared first on Towards Data Science.
How Vision Language Models Are Trained from “Scratch”
Towards Data Science / 3/14/2026
💬 OpinionIdeas & Deep AnalysisModels & Research
Key Points
- The article offers a detailed walkthrough of how text-only language models can be extended to process images by fine-tuning for multimodal capabilities.
- It discusses the typical data requirements, training objectives, and architectural adjustments used to align textual and visual representations.
- It addresses practical considerations such as compute costs, data quality, and evaluation metrics when training vision-language models.
- It explains design choices for fusing visual features with language models and the trade-offs involved in preserving language performance.
- It explores consequences for applications, research directions, and potential industry impact of vision-language modeling.
広告
Related Articles
STADLER reshapes knowledge work at a 230-year-old company
OpenAI Blog
AI Research Is Getting Harder to Separate From Geopolitics
Wired
Sparse Federated Representation Learning for circular manufacturing supply chains with zero-trust governance guarantees
Dev.to
Meet Claude Mythos: Leaked Anthropic post reveals the powerful upcoming model
Reddit r/artificial
**Optimizing AI Agents: A Little-Known Technique to Improve
Dev.to
