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Proposer
Alessandro Suglia
Title
A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning
Goal
Develop chart understanding capabilities for Large Language Models
Description
Investigate resources that can be used to create large language models that can understand, and manipulate different forms of charts in an interactive way.
Resources
https://arxiv.org/abs/2305.14761
Background
AI, Machine Learning, Natural Language Processing
Url
Difficulty Level
Moderate
Ethical Approval
None
Number Of Students
1
Supervisor
Alessandro Suglia
Keywords
deep learning, neural networks, language models, computer vision
Degrees
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Data Science
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