HELM LLM Benchmarking Framework

A HELM LLM Benchmarking Framework is a LLM benchmarking system that aims to improve the transparency and understanding of large language models (LLMs) by evaluating them across multiple scenarios and metrics.

• Context:
  • It can (typically) evaluate Large Language Models across 42 different scenarios, covering tasks such as Question Answering, Summarization, and Toxicity Detection.
  • It can (often) utilize a multi-metric approach to assess not only Accuracy but also Calibration, Robustness, Fairness, Bias, and Efficiency.
  • It can range from evaluating models like GPT-3 to models from organizations such as AI21 Labs, Anthropic, BigScience, and Google.
  • It can facilitate the comparison of Language Models under consistent conditions, ensuring fairness in evaluation.
  • It can highlight trade-offs and performance characteristics of different language models, aiding in their understanding and development.
  • It can support research in Foundation Models by providing comprehensive and standardized benchmarking data.
  • It can inform the deployment of LLMs by evaluating their performance on societal impact metrics.
  • It can include both core scenarios and targeted evaluations to provide a holistic understanding of LLM capabilities and risks.
  • ...
• Example(s):
  • an evaluation of the GPT-3 model on tasks like summarization and question answering, providing insights into its strengths and weaknesses.
  • a benchmarking report comparing the performance of models from different organizations such as Google and OpenAI on fairness and bias metrics.
  • ...
• Counter-Example(s):
  • EleutherAI Harness (Hugging Face) .
• See: Large Language Models, Benchmarking, Artificial Intelligence, Machine Learning

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References

2022

• (Stanford, 2022) ⇒ Stanford University. (2022). "Stanford debuts first AI benchmark to help understand LLMs." In: HAI. [URL](https://hai.stanford.edu/news/stanford-debuts-first-ai-benchmark-help-understand-llms)
  • NOTE: It details the launch and purpose of the HELM project, emphasizing its role in standardizing the evaluation of large language models.
  • QUOTE: HAI’s Center for Research on Foundation Models launches Holistic Evaluation of Language Models (HELM), the first benchmarking project aimed at improving the transparency of language models and the broader category of foundation models.

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