Summary of Openfactcheck: a Unified Framework For Factuality Evaluation Of Llms, by Hasan Iqbal et al.
OpenFactCheck: A Unified Framework for Factuality Evaluation of LLMs
by Hasan Iqbal, Yuxia Wang, Minghan Wang, Georgi Georgiev, Jiahui Geng, Iryna Gurevych, Preslav Nakov
First submitted to arxiv on: 6 Aug 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes OpenFactCheck, a unified framework for assessing the factual accuracy of large language model (LLM) outputs. The framework consists of three modules: RESPONSEEVAL, LLMEVAL, and CHECKEREVAL. These modules enable users to customize automatic fact-checking systems, assess the factuality of input documents, and evaluate LLMs’ overall factuality. OpenFactCheck is open-sourced as a Python library and web service, allowing for public use and further development. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are being used in many real-world applications, but they often make mistakes. This paper creates a tool to check if what the model says is true or not. The tool has three parts: one for checking individual statements, one for checking how well a model does overall, and one for testing other fact-checking systems. The tool is open-source and available online. |
Keywords
» Artificial intelligence » Large language model
