Summary of A Dual-way Enhanced Framework From Text Matching Point Of View For Multimodal Entity Linking, by Shezheng Song et al.
A Dual-way Enhanced Framework from Text Matching Point of View for Multimodal Entity Linking
by Shezheng Song, Shan Zhao, Chengyu Wang, Tianwei Yan, Shasha Li, Xiaoguang Mao, Meng Wang
First submitted to arxiv on: 19 Dec 2023
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Vision and Pattern Recognition (cs.CV)
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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 presents a novel approach to Multimodal Entity Linking (MEL), which links ambiguous mentions with multimodal information to entities in Knowledge Graphs like Wikipedia. The existing methods are limited by modality impurity, such as noise in raw images and ambiguous textual entity representations. To address this, the authors formulate MEL as a neural text matching problem, where each multimodal query is mapped to relevant entities from candidate lists. The proposed DWE framework refines queries with multimodal data, bridges semantic gaps using cross-modal enhancers, and leverages fine-grained image attributes to enhance visual features. Additionally, it enriches entity semantics by incorporating Wikipedia descriptions. Experimental results on three public benchmarks demonstrate state-of-the-art performance, highlighting the superiority of the DWE model. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Multimodal Entity Linking is a way to connect words or phrases with pictures and other information in large databases like Wikipedia. This helps us understand and organize lots of data more effectively. The current methods have some problems, like noisy images and unclear text descriptions. Researchers came up with a new approach that uses special computers called neural networks to match these multimodal queries with the correct information from the database. Their method, called DWE, is very good at solving this problem because it combines text and image information in a smart way. |
Keywords
» Artificial intelligence » Entity linking » Semantics
