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It would also substantially disrupt the generation process: a model which sees B0ris and not Boris is going to struggle to actually associate that input to the
by XorNot 1y ago
It would also substantially disrupt the generation process: a model which sees B0ris and not Boris is going to struggle to actually associate that input to the politician since it won't be well represented in the training set (and on the output side the same: if it does make the association, a reasoning model for example would include the proper name in the output first at which point the supervisor process can reject it).
- quonn 1y agoI don‘t think so. My impression with LLMs is that they correct typos well. I would imagine this happens in early layers without much impact on the remaining computation.
- lupire 1y ago"Draw a picture of a gorgon with the face of the 2024 Prime Minister of UK."
- chgs 1y agoThere were two.
- binarymax 1y agoNo it doesn't disrupt. This is a well known capability of LLMs. Most models don't even point out a mistake they just carry on. https://chatgpt.com/share/686b1092-4974-8010-9c33-86036c88e789 https://chatgpt.com/share/686b1092-4974-8010-9c33-86036c88e7...