Deciphering language processing in the human brain through LLM representations
(research.google)
Large Language Models (LLMs) optimized for predicting subsequent utterances and adapting to tasks using contextual embeddings can process natural language at a level close to human proficiency. This study shows that neural activity in the human brain aligns linearly with the internal contextual embeddings of speech and language within large language models (LLMs) as they process everyday conversations.
Large Language Models (LLMs) optimized for predicting subsequent utterances and adapting to tasks using contextual embeddings can process natural language at a level close to human proficiency. This study shows that neural activity in the human brain aligns linearly with the internal contextual embeddings of speech and language within large language models (LLMs) as they process everyday conversations.