I am once again shocked at how much better image retrieval performance you can get if you embed highly opinionated summaries of an image, a summary that came out of a visual language model, than using CLIP embeddings themselves. If you tell the LLM that the summary is going to be embedded and used to do search downstream. I had one system go from 28% recall at 5 using CLIP to 75% recall at 5 using an LLM summary.
Recent articles
- Wilson Lin on FastRender: a browser built by thousands of parallel agents - 23rd January 2026
- First impressions of Claude Cowork, Anthropic's general agent - 12th January 2026
- My answers to the questions I posed about porting open source code with LLMs - 11th January 2026