[R] Compression Represents Intelligence Linearly

**Paper**: [https://arxiv.org/abs/2404.09937](https://arxiv.org/abs/2404.09937)

**Code**: [https://github.com/hkust-nlp/llm-compression-intelligence](https://github.com/hkust-nlp/llm-compression-intelligence)

**Datasets**: [https://huggingface.co/datasets/hkust-nlp/llm-compression](https://huggingface.co/datasets/hkust-nlp/llm-compression)

**Abstract**:

>There is a belief that learning to compress well will lead to intelligence. Recently, language modeling has been shown to be equivalent to compression, which offers a compelling rationale for the success of large language models (LLMs): the development of more advanced language models is essentially enhancing compression which facilitates intelligence. Despite such appealing discussions, little empirical evidence is present for the interplay between compression and intelligence. In this work, we examine their …

abstract advanced belief compression development discussions evidence intelligence language language models large language large language models llms machinelearning modeling success will