HELM

语言模型采用文本并生成文本: 尽管语言模型很简单，但它正越来越多地充当从问题回答到摘要的几乎所有语言技术的基础。但是他们的巨大能力和风险还没有得到很好的理解。语言模型的整体评估 (HELM) 是一个活着的基准，旨在提高语言模型的透明度。

Language models take text as input and generate text as output. Despite their conceptual simplicity, they are increasingly serving as the foundational underpinning for nearly all language technologies ranging from question answering to text summarization. However, their substantial capabilities and associated risks remain poorly understood. The Holistic Evaluation of Language Models (HELM) is a living benchmark designed to enhance the transparency of language models.

搜集汇总

背景与挑战

背景概述

HELM（语言模型的整体评估）是由斯坦福大学于2022年发布的一个开源基准数据集，采用Apache 2.0许可证，大小为802.0B。该数据集旨在通过全面评估语言模型的能力和风险，提高其透明度，覆盖问题回答、摘要等多种语言技术应用，是一个持续更新的活着的基准工具。