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I guess one technique is to train a model on various language model outputs to classify these as good/bad/intriguing/robot-sounding/repetitive/etc. A human can
by antoineMoPa 4y ago
I guess one technique is to train a model on various language model outputs to classify these as good/bad/intriguing/robot-sounding/repetitive/etc. A human can tag the answers for the training dataset.
Then, we can use this model to compare different LLMs and optimize new models - could be with genetic algorithms or just a human tweaking the model - so that the LLM maximizes whatever we want.
- visarga 4y agoYou just rediscovered RLHF - reinforcement learning from human preferences. That's the last stage of training for chatGPT, but uses RL instead of supervised learning.