Llama – MIT EECS

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MIT-IBM Watson AI Lab researchers have developed a universal guide for estimating how large language models will perform based on smaller models in the same family.

In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.

How to build AI scaling laws for efficient LLM training and budget maximization

Unpacking the bias of large language models