Zero-Shot Cross-Lingual Document-Level Event Causality Identification with Heterogeneous Graph Contrastive Transfer Learning

arXiv:2403.02893v1 Announce Type: new
Abstract: Event Causality Identification (ECI) refers to detect causal relations between events in texts. However, most existing studies focus on sentence-level ECI with high-resource language, leaving more challenging document-level ECI (DECI) with low-resource languages under-explored. In this paper, we propose a Heterogeneous Graph Interaction Model with Multi-granularity Contrastive Transfer Learning (GIMC) for zero-shot cross-lingual document-level ECI. Specifically, we introduce a heterogeneous graph interaction network to model the long-distance dependencies between events that are scattered over document. …

abstract arxiv causality cross-lingual cs.ai cs.cl deci document event events focus graph identification language languages low paper relations studies transfer transfer learning type zero-shot