Papers by Fangqi Zhu

2 papers
A Diffusion Model for Event Skeleton Generation (2023.findings-acl)

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Challenge: Existing methods for event schema generation are noise-sensitive and error-accumulating, e.g., inability to correct errors while generating schema.
Approach: They propose a novel diffusion event graph model that embeds and roundes event graphs into learnable latent representations and a denoising process to maintain the model's robustness.
Outcome: The proposed model achieves better results than existing state-of-the-art models on three IED bombing datasets.
Learning to Describe for Predicting Zero-shot Drug-Drug Interactions (2023.emnlp-main)

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Challenge: Existing computational methods for DDI prediction fail to capture interactions for new drugs due to the lack of knowledge.
Approach: They propose a problem setup as zero-shot DDI prediction that deals with the case of new drugs by using textual information from online databases.
Outcome: The proposed method improves on several settings including zero-shot and few-shot DDI prediction and the selected texts are semantically relevant.

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