Hallucination isn’t something that disappears just because you’ve got good precision but poor recall. Nope — it’ll still happen even if the context looks “sufficient.”
Now, I’m not entirely sure how sufficient is defined in the paper, but one thing’s clear: completeness in what you feed the LLM matters.
Sure, when you’re firing queries at an agent with a half-decent retrieval system, it feels like things are working — but without benchmarking, you’re basically lurking in the land of unknown unknowns.
Life is really about appreciating the obvious, especially when it’s dressed up in funky phrases. You know what I mean. And here the “obvious” is just another reminder: the quality of retrieval you provide to LLMs makes or breaks the outcome.
Now, this paper is a refreshing read for anyone who still thinks hallucination is some ancient relic and that current retrieval infra will magically solve enterprise problems.
Just hire a bunch of expensive AI folks, sprinkle in some buzzwords, and voilà — the “ultimate” retrieval-contextual-domain-specific-agentic-RAG framework to solve all your client needs!