3 ms·
Interestingly, there's a decent chance I'd remember if there was an out of context passage saying "the password is FooBar". I wonder if it would be better to te
by foota 3y ago
Interestingly, there's a decent chance I'd remember if there was an out of context passage saying "the password is FooBar". I wonder if it would be better to test with minor edits? E.g., "what color shirt was X wearing when..."
- ambichook 3y agoi feel you would recognise that more as a quirk of how humans think, remember that LLMs think fundamentally differently to you and i. i would be curious about someone making a benchmark like that and using it to compare as an experiment however
- foota 3y agoI'm not trying to anthropomorphize the model, but it's not hard to imagine that a model would attribute significance to something completely out of context, and hence "focus" on it when computing attention. Another possible synthetic benchmark would be to present a list of key value pairs and then ask it for the value corresponding to different keys. Or present a long list of distinct facts and then ask it about them. This latter one could probably be sourced from something like a trivia question and answers data set. I bet there's something like that from Jeopardy.
- kenjackson 3y agoI think instead you could just do a full doc of relationships. "Tina and Chris have five children named ..." Then you can ask it who is Tina's (great)^57 grandmother's twice removed cousin on her father's side? It would have to be able to remember the context of the relationships up and down the document and there'd be nothing to key into as you could ask about any relationship.