Papers by Haoyuan Peng

3 papers
Grafting Pre-trained Models for Multimodal Headline Generation (2022.emnlp-industry)

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Challenge: Existing approaches to generate video headlines with pre-trained language models are labor intensive and impractical.
Approach: They propose to graft the encoder from the pre-trained video-language model on the generative pre-trainer model and propose a consensus fusion mechanism for the integration of different components.
Outcome: The proposed model achieves strong results on a brand-new dataset collected from real-world applications.
DB-Explore: Automated Database Exploration and Instruction Synthesis for Text-to-SQL (2025.findings-emnlp)

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Challenge: Recent text-to-SQL systems that use large language models struggle with complex database structures and domain-specific queries.
Approach: a framework that aligns large language models with database knowledge is proposed . DB-Explore constructs database graphs to capture complex relational schemas .
Outcome: a new framework outperforms existing text-to-SQL systems by outperforming existing systems.
VKIE: The Application of Key Information Extraction on Video Text (2023.emnlp-industry)

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Challenge: Existing methods for extracting structured information from videos are coarse-grained at segment level and unable to capture finegrained information at the entity level.
Approach: They propose a task for extracting hierarchical key information from visual texts on videos . they decouple the task into four subtasks and propose two implementation solutions .
Outcome: The proposed solutions achieve remarkable performance and efficient inference speed on a well-defined dataset.

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