Language in Vivo vs. in Silico: Size Matters but Larger Language Models Still Do Not Comprehend Language on a Par with Humans

arXiv:2404.14883v1 Announce Type: new
Abstract: Understanding the limits of language is a prerequisite for Large Language Models (LLMs) to act as theories of natural language. LLM performance in some language tasks presents both quantitative and qualitative differences from that of humans, however it remains to be determined whether such differences are amenable to model size. This work investigates the critical role of model scaling, determining whether increases in size make up for such differences between humans and models. We test …

abstract act arxiv cs.cl differences humans language language models large language large language models llm llm performance llms natural natural language performance quantitative tasks type understanding