水准点(测量)
重要事件
计算机科学
稳健性(进化)
人工智能
集合(抽象数据类型)
插件
程序设计语言
大地测量学
生物化学
历史
基因
考古
化学
地理
作者
Grégoire Mialon,Clémentine Fourrier,Craig Swift,Thomas Wolf,Yann LeCun,Thomas Scialom
标识
DOI:10.48550/arxiv.2311.12983
摘要
We introduce GAIA, a benchmark for General AI Assistants that, if solved, would represent a milestone in AI research. GAIA proposes real-world questions that require a set of fundamental abilities such as reasoning, multi-modality handling, web browsing, and generally tool-use proficiency. GAIA questions are conceptually simple for humans yet challenging for most advanced AIs: we show that human respondents obtain 92\% vs. 15\% for GPT-4 equipped with plugins. This notable performance disparity contrasts with the recent trend of LLMs outperforming humans on tasks requiring professional skills in e.g. law or chemistry. GAIA's philosophy departs from the current trend in AI benchmarks suggesting to target tasks that are ever more difficult for humans. We posit that the advent of Artificial General Intelligence (AGI) hinges on a system's capability to exhibit similar robustness as the average human does on such questions. Using GAIA's methodology, we devise 466 questions and their answer. We release our questions while retaining answers to 300 of them to power a leader-board available at https://huggingface.co/gaia-benchmark.
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