Papers by Xinjiang Lu

2 papers
A Table-to-Text Framework with Heterogeneous Multidominance Attention and Self-Evaluated Multi-Pass Deliberation (2023.findings-emnlp)

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Challenge: Table-to-text works have been widely applied in different domains, such as weather forecast and financial report generation.
Approach: They propose a table-to-text approach on top of Self-evaluated multi-pass Generation and Heterogenous Multidominance Attention to explore the hierarchical structure.
Outcome: The proposed method outperforms several SOTA methods quantitatively and qualitatively on three public datasets.
Towards Table-to-Text Generation with Pretrained Language Model: A Table Structure Understanding and Text Deliberating Approach (2022.emnlp-main)

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Challenge: Currently, the generalization issues hinder the applicability of neural table-to-text models due to the limited source tables.
Approach: They propose a table-structureaware text generation model with pretrained language model and propose TASD to bridge the gap between the structured table and text input.
Outcome: The proposed model bridges the gap between the structured table and text input and generates accurate and fluent descriptive texts on two public datasets.

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