Moral Self-Correction in Large Language Models | paper explained

We explain why large language models (LLM) suffer from multiple personality disorder and how they can morally self-correct with instructions. We elucidate technical terms such as RLHF (reinforcement learning from human feedback), explain "instruction following" and "Chain of Thought" prompting (CoT). "Moral Self-Correction in Large Language Models", paper explained.
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📜 Ganguli, Deep, Amanda Askell, Nicholas Schiefer, Thomas Liao, Kamilė Lukošiūtė, Anna Chen, Anna Goldie et al. "The capacity for moral self-correction in large language models." arXiv preprint arXiv:2302.07459 (2023). https://arxiv.org/abs/2302.07459

Read more about RLHF: https://huggingface.co/blog/rlhf 🤗

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Outline:
00:00 Large LMs are biased
01:48 Salad (Sponsor)
02:49 Question answering: Q
04:23 Language models have multiple personality disorder
05:27 RLHF explained
08:23 Instruction Following (IF) explained
09:37 CoT: Chain of Thought prompting explained
10:05 Effect of size on moral self-correction
13:07 Effect of RLHF on instruction following
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