5 ms·
The Olaf Scholz exemple from this article is just another exemple of how LLMs can’t count. If you try this prompt: “In this list of words: bike, apple, phone, d
by maaaaattttt 3y ago
The Olaf Scholz exemple from this article is just another exemple of how LLMs can’t count. If you try this prompt: “In this list of words: bike, apple, phone, dirt, tee, sun, glass; which is the fifth word?” it will fail as well. “Fifth” is not connected to any counting ability in LLMs the way it is for us.
If you now try this prompt: “Who’s Tom Cruise’s mother in this exemple: “Mary Lee Pfeiffer is Tom Cruise’s mother.”?” It will give you the right answer.
IMO this is a sign that it can understand reversibility.
The exemple used are not present enough in the dataset and the “confidence” of the model is not high enough for it to give the right answer. Or, as stated at the beginning they use counting mechanisms (or others) that the model just doesn’t have.
- saliagato 3y agoIt can’t count because what the LLM sees is a bunch of tokens not words
- maaaaattttt 3y agoExactly. And asking what/who/which is the “Ninth” something will always fail (or randomly succeed)
- OJFord 3y agoMuch more likely to work for something like German chancellors, US presidents, etc. that people do actually number and could easily have been trained on that data. If you ask 'who was the 45th US president' it doesn't need to be able to count a list of US presidents to answer 'Trump', you can just duckduckgo that and get the answer anyway, that's not doing any counting either.
- deleted 3y ago[deleted]