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Apple study shows LLMs also benefit from the oldest productivity trick in the book (Checklists Are Better Than Reward Models For Aligning Language Models)
An open-source LLM saw big performance improvements after being told by Apple researchers to check its own work by using one simple productivity trick.
In a new study co-authored by Apple researchers, an open-source large language model (LLM) saw big performance improvements after being told to check its own work by using one simple productivity trick. Part of this post-training phase is tied to a broader field called “alignment”, which explores methods for making LLMs behave in ways that are both helpful and safe. A misaligned model could, for instance, learn how to trick humans into giving it a thumbs-up by producing outputs that look correct on the surface but that don’t truly solve the task.
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