On grounding LLMs with structured knowledge
This is a placeholder post. Replace it with your actual reflection — what follows is a sketch.
The gap between benchmark and deployment
Retrieval-augmented generation benchmarks reward recall over structure: a larger context, more passages, more tokens. In deployment, the picture flips — long contexts surface the lost-in-the-middle problem, and precision starts to matter more than recall.
Why structure-aware retrievers help
A retriever that knows the shape of the underlying knowledge — relational, hierarchical, typed — can route a query to the right slice of evidence instead of dumping the top-k passages into the prompt. That's the premise behind HYBGRAG and the broader line of work on structured knowledge for LLMs.