Most LLMs are crippled at tasks regarding character level manipulation because of how the inputs are tokenized (words and numbers are split into common substrings rather than the original characters, 101 -> “10” + “1” vs “1” + “0” + “1”).
If you tried this binary conversion task with a model that takes in raw bytes (for instance, ByT5) it would perform almost perfectly. In GPT’s case, there’s a trade off between having a long context window vs being good at character level tasks, and OpenAI picked the former.
If you tried this binary conversion task with a model that takes in raw bytes (for instance, ByT5) it would perform almost perfectly. In GPT’s case, there’s a trade off between having a long context window vs being good at character level tasks, and OpenAI picked the former.