Papers by Tianqi Hu

1 papers
Event Representation Learning with Multi-Grained Contrastive Learning and Triple-Mixture of Experts (2024.lrec-main)

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Challenge: Existing methods for learning event representations fail to capture hidden feature information between events.
Approach: They propose a method that extends the random masked language model by incorporating a specialized MLM to capture different grammatical structures within events.
Outcome: The proposed method outperforms baselines in hard similarity and transitive sentence similarity tasks, highlighting the superiority of the proposed method.

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