3 ms·

Worth trying to show some examples of critical thinking to LLM and then see what happens on new set of data points

• lukev 3y ago
  This definitely works. There's lots of papers on this. Heck, you can verify this with ChatGPT yourself... just ask it a couple questions, then (in a separate thread) ask the same questions but tell it to "think step by step" as an instruction. It performs visibly better. The point is it fundamentally, at the end of the day, it's generating one token at a time with only its prompt and previously generated tokens for input. If you can inject other information/facts into the context, or even context from another model instance that have a different "train of thought", you can in theory get better results than the model itself generating a sequence. Look up Chain of Thought / Tree of Thought / Graph of Thought for an intro, as well as basically anything on retrieval augmented generation (RAG) or LLM tool usage.
  • ddmma 3y ago
    Thanks for pointing out the evaluation methods and actually being doing some metrics on the outcome from LLMs myself. I bet more on now adjusted knowledge on top of generated content based on facts/ nonsense scoring that can be harvested for feeding reasoning graphs with kind of auto balancing. Less resources and high impact will make the difference on long term.