Papers by Yuguang Wang

2 papers
Event Extraction as Multi-turn Question Answering (2020.findings-emnlp)

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Challenge: Current approaches to event extraction fail to model rich interactions among event types and arguments of different roles.
Approach: They propose a new paradigm that formulates event extraction as multi-turn question answering . they propose to use reading comprehension problems to extract triggers and arguments .
Outcome: The proposed approach outperforms current state-of-the-art on argument extraction tasks . it makes full use of dependency among arguments and event types, and generalizes well .
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering (2025.coling-industry)

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Challenge: Deep learning models are often inefficient and resource-intensive for biologists without specialized computational expertise.
Approach: They propose an agent framework that leverages large language models for multimodal automated machine learning (AutoML) in protein engineering.
Outcome: The proposed framework demonstrates significant improvements in performance over previous approaches in two real-world protein engineering tasks.

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