Summary of Multimodal Adaptive Inference For Document Image Classification with Anytime Early Exiting, by Omar Hamed et al.
Multimodal Adaptive Inference for Document Image Classification with Anytime Early Exiting
by Omar Hamed, Souhail Bakkali, Marie-Francine Moens, Matthew Blaschko, Jordy Van Landeghem
First submitted to arxiv on: 21 May 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Computation and Language (cs.CL); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel approach to visually-rich document understanding (VDU) tasks, aiming to strike a balance between performance and efficiency in production environments. The authors design a multimodal early exit (EE) model that incorporates various training strategies, exit layer types, and placements to achieve a Pareto-optimal balance between predictive performance and efficiency for multimodal document image classification. Experimental results show an improved performance-efficiency trade-off, with a reduction of over 20% in latency while retaining baseline accuracy. The study represents the first exploration of multimodal EE design within the VDU community and highlights the effectiveness of calibration in improving confidence scores for exiting at different layers. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us understand documents better by making computers work smarter, not harder! Currently, we rely on big models that are great but slow. The authors created a new way to make computers do tasks with documents, called multimodal early exit (EE), which is fast and still good at understanding. They tested it and found that it’s actually faster than before while keeping the same level of accuracy! This matters because we want to use computers to help us understand documents quickly and accurately. |
Keywords
» Artificial intelligence » Image classification
