2 citations · 5 across the 6 of their papers we have counts for
7 papers · 1 filter
A Generative Approach for Script Event Prediction via Contrastive Fine-tuning
Fangqi Zhu, Jun Gao, Changlong Yu +5
Script event prediction aims to predict the subsequent event given the context. This requires the capability to infer the correlations between events. Recent works have attempted t…
Title2Event: Benchmarking Open Event Extraction with a Large-scale Chinese Title Dataset
Haolin Deng, Yanan Zhang, Yangfan Zhang +9
Event extraction (EE) is crucial to downstream tasks such as new aggregation and event knowledge graph construction. Most existing EE datasets manually define fixed event types and…
An Empirical Revisiting of Linguistic Knowledge Fusion in Language Understanding Tasks
Changlong Yu, Tianyi Xiao, Lingpeng Kong +2
Though linguistic knowledge emerges during large-scale language model pretraining, recent work attempt to explicitly incorporate human-defined linguistic priors into task-specific…
Improving Event Representation via Simultaneous Weakly Supervised Contrastive Learning and Clustering
Jun Gao, Wei Wang, Changlong Yu +3
Representations of events described in text are important for various tasks. In this work, we present SWCC: a Simultaneous Weakly supervised Contrastive learning and Clustering fra…
When Hearst Is not Enough: Improving Hypernymy Detection from Corpus with Distributional Models
Changlong Yu, Jialong Han, Peifeng Wang +4
We address hypernymy detection, i.e., whether an is-a relationship exists between words (x, y), with the help of large textual corpora. Most conventional approaches to this task ha…
Enriching Large-Scale Eventuality Knowledge Graph with Entailment Relations
Changlong Yu, Hongming Zhang, Yangqiu Song +2
Computational and cognitive studies suggest that the abstraction of eventualities (activities, states, and events) is crucial for humans to understand daily eventualities. In this…