/plushcap/analysis/arize/arize-trustworthy-llms-a-survey-and-guideline-for-evaluating-large-language-models-alignment

Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment

What's this blog post about?

In this paper review, we discussed how to create a golden dataset for evaluating LLMs using evals from alignment tasks. The process involves running eval tasks, gathering examples, and fine-tuning or prompt engineering based on the results. We also touched upon the use of RAG systems in AI observability and the importance of evals in improving model performance.

Company
Arize

Date published
May 29, 2024

Author(s)
Sarah Welsh

Word count
8093

Language
English

Hacker News points
None found.


By Matt Makai. 2021-2024.