Paper Image

Evaluating multimodal AI assistants through standardized tests

Published on:

5 November 2023

Primary Category:

Computer Vision and Pattern Recognition

Paper Authors:

Zhelun Shi,

Zhipin Wang,

Hongxing Fan,

Zhenfei Yin,

Lu Sheng,

Yu Qiao,

Jing Shao


Key Details

Presents ChEF - Comprehensive Evaluation Framework for multimodal AI

ChEF has 4 modular components: Scenarios, Instructions, Inferences, Metrics

ChEF evaluates on 9 datasets and 6 key capabilities like robustness

Tests 9 multimodal AI assistants, revealing strengths and weaknesses

Framework enables standardized comparison and inspires advancement

AI generated summary

Evaluating multimodal AI assistants through standardized tests

This paper introduces a comprehensive framework to evaluate multimodal AI assistants. It tests assistants across various datasets and on key capabilities like following instructions, learning from examples, and handling noisy inputs.

Answers from this paper


No comments yet, be the first to start the conversation...

Sign up to comment on this paper

Sign Up