Papers by Xiangyuan Guan

2 papers
XFormParser: A Simple and Effective Multimodal Multilingual Semi-structured Form Parser (2025.coling-main)

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Challenge: Document AI parsing semi-structured image form is a key information extraction task.
Approach: They propose a multimodal and multilingual semi-structured FORM PARSER which integrates SER and relation extraction into a unified framework.
Outcome: The proposed framework achieves up to 1.79% improvement on RE tasks in multilingual and zero-shot settings.
M3TQA: Massively Multilingual Multitask Table Question Answering (2026.findings-acl)

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Challenge: Existing multilingual table benchmarks suffer from geolinguistic imbalance - overrepresenting certain languages and lacking sufficient scale for rigorous cross-lingual analysis.
Approach: They propose a framework for massively multilingual table question answering that includes tables expanded to 97 languages from Chinese and English sources.
Outcome: Experiments on state-of-the-art LLMs show that synthetically generated training data significantly boosts performance, especially for low-resource languages.

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