GAIA - chunhualiao/public-docs GitHub Wiki
GAIA (General AI Assistants) benchmark consists of 466 questions designed to evaluate next-generation LLMs with augmented capabilities[1][3]. These tasks assess fundamental abilities such as:
- Reasoning
- Multi-modality handling
- Web browsing
- Tool-use proficiency
The questions in GAIA are conceptually simple for humans but challenging for AI systems[3]. They simulate real-world applications and require multiple reasoning steps to answer[9]. Some key features of GAIA tasks include:
- Text-based questions, sometimes accompanied by files like images or spreadsheets[6]
- Questions that often require the use of tools such as web browsers and code interpreters[9]
- Tasks that may involve handling multi-modal inputs (e.g., images, videos, excel sheets)[9]
- Questions designed to have unique, factual answers, allowing for simple and robust automatic evaluation[6]
GAIA's approach differs from traditional AI benchmarks by focusing on tasks that are deceptively simple for humans but intricate for AI, aiming to push AI towards the next generation of capabilities[1].
Citations:
- [1] https://klu.ai/glossary/gaia-benchmark-eval
- [2] https://www.ibm.com/think/insights/llm-evaluation
- [3] https://ai.meta.com/research/publications/gaia-a-benchmark-for-general-ai-assistants/
- [4] http://arxiv.org/abs/2311.12983v1
- [5] https://aisera.com/blog/llm-evaluation/
- [6] https://sandbox.getindico.io/event/3788/contributions/2784/attachments/1283/1797/2311.12983v1%20(1).pdf
- [7] https://www.linkedin.com/pulse/next-generation-llm-evaluation-bridging-academic-benchmarks-jha-w1cmf
- [8] https://huggingface.co/papers/2311.12983
- [9] https://arduin.io/blog/gaia-overview/