Summary of From Linguistic Giants to Sensory Maestros: a Survey on Cross-modal Reasoning with Large Language Models, by Shengsheng Qian et al.
From Linguistic Giants to Sensory Maestros: A Survey on Cross-Modal Reasoning with Large Language Models
by Shengsheng Qian, Zuyi Zhou, Dizhan Xue, Bing Wang, Changsheng Xu
First submitted to arxiv on: 19 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG); Multimedia (cs.MM)
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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 The paper presents a comprehensive survey on the application of Large Language Models (LLMs) in Cross-Modal Reasoning (CMR). It provides a detailed taxonomy of current methodologies used in CMR and discusses design strategies, operational techniques, and challenges. The survey aims to advance the field by offering a holistic view of current research and identifying potential areas for future exploration. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Cross-modal reasoning is an important skill for artificial intelligence systems. Large Language Models are designed to understand human language. Researchers have started using these models to tackle cross-modal reasoning tasks. This paper looks at how LLMs can be used in CMR, including the different approaches and challenges that come with it. |
