Papers by Quanwei Tang

2 papers
Don’t Just Listen, Try Planning: Graph-based Retrieval-Generation Agent for Long-form Audio Meeting Understanding (2026.findings-acl)

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Challenge: Existing question answering (QA) datasets for long audio meetings suffer from acoustic information loss and poor long-term dependency capture.
Approach: They propose a question answering dataset that captures three core dimensions of long-form audio meeting content.
Outcome: The proposed model captures three core dimensions of long-form audio meeting content: complex semantics, multi-speaker interactions, and quite long timestamps.
A Comprehensive Graph Framework for Question Answering with Mode-Seeking Preference Alignment (2025.findings-acl)

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Challenge: Existing studies struggle with achieving global understanding of large language models . GraphMPA is a graph-based framework with mode-seeking preference alignment .
Approach: They propose a graph-based framework with mode-seeking preference alignment to improve model outputs.
Outcome: The proposed framework constructs a hierarchical document graph mimicking human cognitive processes for information understanding and synthesis.

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