I don’t understand how this is a different result than giving any LLM a task that is not completely grounded? I’ve observed this in coding tasks, if I forget to include a file referred to in the spec, the LLM will just hallucinate a version of it and my results suck. If I give it the file (and really, all the information I claimed it had access to), the task works fine. I fixed this in my pipeline with a prompt that does an extensive grounding analysis to determine if the assets I’m giving it are complete with respect to the spec (and that the spec is grounded as well, ie it doesn’t refer to something that is undefined).
I wonder if the above problem can be fixed similarly? Just ask the LLM to do a conservative grounding analysis before jumping to the main task?
It's not different- there's a line of research and reasoning where people who don't use LLM's regularly point out issues that have been known (and more or less solved) for more than a year now (which is an eternity in the LLM space).