Papers by Yongping Xiong

3 papers
LayoutPointer: A Spatial-Context Adaptive Pointer Network for Visual Information Extraction (2024.naacl-long)

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Challenge: Existing models inadequately utilize spatial information of entities, causing incorrectly linking spatially distant entities.
Approach: They propose a Spatial-Context Adaptive Pointer Network to restore semantic order among entities . they propose XFUND-based tail-to-head pointer to restore the semantic order .
Outcome: The proposed method outperforms existing state-of-the-art methods in F1 scores for RE tasks.
MegaPairs: Massive Data Synthesis for Universal Multimodal Retrieval (2025.acl-long)

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Challenge: despite the growing demand for multimodal retrieval, there is a lack of training data.
Approach: They propose a data synthesis method that leverages vision language models and open-domain images to generate high-quality data.
Outcome: The proposed method outperforms baseline models on 70 more datasets and can scale up.
VISTA: Visualized Text Embedding For Universal Multi-Modal Retrieval (2024.acl-long)

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Challenge: Existing methods for multimodal retrieval are mostly text-oriented, which lack the capability to process visual information.
Approach: They propose a multi-modal multi-text embedding model VISTA which extends a powerful text encoder with the image understanding capability by introducing visual token embedds.
Outcome: The proposed model achieves superior performance across a variety of multi-modal retrieval tasks in zero-shot and supervised settings.

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