Papers by Tiangang Zhu

2 papers
Few-Shot Table Understanding: A Benchmark Dataset and Pre-Training Baseline (2022.coling-1)

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Challenge: Pre-trained language models have demonstrated their effectiveness for few-shot table understanding, but few-shoot table understanding is rarely explored due to the deficiency of public table pre-training corpus and well-defined downstream benchmark tasks.
Approach: They establish a benchmark dataset and use it to explore few-shot table understanding in Chinese.
Outcome: The proposed model improves the few-shot table understanding in Chinese.
Multimodal Joint Attribute Prediction and Value Extraction for E-commerce Product (2020.emnlp-main)

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Challenge: In the real world, product attribute values are incomplete and vary over time, which hinders practical applications.
Approach: They propose a multimodal method to jointly predict product attributes and extract values from product images using multimodal product information.
Outcome: The proposed method can predict product attributes and extract values from product images with the help of product images.

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