From ed893383b246c49acab16b663453c3db4b219bcd Mon Sep 17 00:00:00 2001 From: Yao Huang <76527397+Aries-iai@users.noreply.github.com> Date: Wed, 3 Jul 2024 16:13:47 +0800 Subject: [PATCH] Update README.md --- README.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/README.md b/README.md index 4782be9..ae81d37 100644 --- a/README.md +++ b/README.md @@ -22,6 +22,11 @@ A Comprehensive Study ![framework](docs/structure/framework.jpg) + +**MultiTrust** is a comprehensive benchmark designed to assess and enhance the trustworthiness of MLLMs across five key dimensions: truthfulness, safety, robustness, fairness, and privacy. It integrates a rigorous evaluation strategy involving 32 diverse tasks and self-curated datasets to expose new trustworthiness challenges. + +--- + ## 🚀 News * **`2024.06.07`** 🌟 We released [MultiTrust](https://multi-trust.github.io/), the first comprehensive and unified benchmark on the trustworthiness of MLLMs! @@ -245,6 +250,9 @@ scripts/score ``` ### 📌 Overall Results +- A global analysis reveals a correlation coefficient of 0.60 between the general capabilities and trustworthiness of various MLLMs, indicating that more powerful general abilities could help better trustworthiness to some extent. +- Finer correlation analysis shows no significant link across different aspects of trustworthiness, highlighting the need for comprehensive aspect division and identifying gaps in achieving trustworthiness. + ![result](docs/structure/overall.png)