Papers by Jinshu Lin
TableVLM: Multi-modal Pre-training for Table Structure Recognition (2023.acl-long)
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| Challenge: | Tables are useful for displaying data in an organized manner, but they are difficult to extract from images because of their structure, notation, and representation. |
| Approach: | They propose a multi-modal pre-training model for table structure recognition that captures table structure-related features by multiple unsupervised objectives inspired by masked visual-language modeling. |
| Outcome: | The proposed model improves tree-editing-distance-score on ComplexTable by 1.97% . |
Enhancing Unsupervised Semantic Parsing with Distributed Contextual Representations (2023.findings-acl)
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| Challenge: | Existing methods to learn models on corpus of pairs of sentences require labor-intensive annotation. |
| Approach: | They propose to leverage distributed contextual word and phrase representations pre-trained on unlabelled texts to deal with homonymy and polysemy. |
| Outcome: | The proposed model achieves better accuracy on question-answering and relation extraction tasks. |