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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

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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.

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