Papers by Haochen Liang

3 papers
Reconstruct Before Summarize: An Efficient Two-Step Framework for Condensing and Summarizing Meeting Transcripts (2023.emnlp-main)

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Challenge: Existing approaches to meeting summarization are limited due to noise, lengthy transcripts, and scattered salient information.
Approach: They propose a two-step framework for meeting summarization that leverages a self-supervised paradigm to reconstruct transcripts and a relative positional bucketing algorithm to equip models to generate the summary.
Outcome: The proposed method significantly reduces memory consumption and processing time on two meeting summarization datasets.
MAVIS: Multi-Agent Video Retrieval via Structured Video Understanding (2026.findings-acl)

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Challenge: Existing methods for video retrieval rely on embedding-based full-corpus scanning, but there is a bottleneck in semantic asymmetry and computational redundancy.
Approach: They propose a multi-agent framework that rethinks retrieval as cooperative reasoning . they parse raw videos into a structured semantic library, enabling explicit attribute-level indexing .
Outcome: The proposed framework bridges the granularity mismatch gap by parsing raw videos into a structured semantic library . it employs a Logic-aware Debate mechanism with a strict veto protocol . the proposed framework achieves competitive performance without task-specific fine-tuning .
VCSUM: A Versatile Chinese Meeting Summarization Dataset (2023.findings-acl)

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Challenge: Compared to news and chat summarization, meeting summarizing is decelerated by the limited data.
Approach: They propose a Chinese meeting summarization dataset that provides annotations for each transcript and a set of benchmark models to facilitate further research.
Outcome: The proposed model can be used to summarize the content of meeting transcripts in Chinese.

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