Papers by Fanqing Meng

2 papers
Equipping Retrieval-Augmented Large Language Models with Document Structure Awareness (2025.findings-emnlp)

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Challenge: Existing approaches to retrieval-augmented generation ignore valuable structure that is crucial for document organization.
Approach: They propose a framework that explicitly incorporates structural information throughout the RAG process.
Outcome: The proposed framework incorporates structural information throughout the RAG process.
ChartAssistant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction Tuning (2024.findings-acl)

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Challenge: Charts are an effective tool for understanding data patterns, but their combination of graphical elements and textual components poses challenges for general-purpose multimodal models.
Approach: They propose a chart-based vision-language model for universal chart comprehension and reasoning that leverages a dataset of chart-related tasks.
Outcome: The proposed model outperforms the state-of-the-art charts with zero-shot setting on various chart tasks.

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