GAIA (General AI Assistants) is a benchmark developed by researchers at Meta, Hugging Face, AutoGPT, and GenAI to evaluate the capabilities of general-purpose AI agents and AI assistants. This benchmark measures how well an AI model can handle real-world tasks, such as human-like reasoning, multimodal processing, web browsing, and the ability to use tools.
Purpose and characteristics of GAIA
- Focus on Real-World Challenges: GAIA evaluates the versatility and flexibility of AI in everyday tasks, unlike traditional benchmarks that test specialized knowledge like law or chemistry.
- Over 450 Questions: GAIA consists of over 450 questions, each with clear correct answers, comprehensively evaluating the diverse capabilities of AI models.
Structure and difficulty of questions
The GAIA questions are divided into three levels, each of which requires different competencies:
- Level 1: Questions that can be answered by advanced LLMs.
- Level 2: Questions that require the use of tools or web searches.
- Level 3: Questions that require complex reasoning and multi-step processing.
Each level contains a public development dataset and a private test set.
Leaderboards and ratings
GAIA’s leaderboard compares the performance of different AI models.
References
- Hugging Face GAIA Page:
https://huggingface.co/gaia-benchmark - Hugging Face Datasets Dataset Details:
https://huggingface.co/datasets/gaia-benchmark/GAIA - Hugging Face Spaces Leaderboard:
https://huggingface.co/spaces/gaia-benchmark/leaderboard - Official Papers (arXiv):
https://arxiv.org/abs/2311.12983
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