G^2C-MT: Graph-Guided Context Selection for Document-Level Machine Translation 事件

G^2C-MT: Graph-Guided Context Selection for Document-Level Machine Translation arXiv:2606.03078v1 Announce Type: new Abstract: Effective document-level machine translation (DocMT) requires capturing long-range discourse dependencies. Recent work has explored retrieval-based and discourse-aware context selection. However, these approaches often lack an explicit mechanism for modeling structured discourse dependencies between distant paragraphs in a document. In this paper, we propose G^2C-MT (Gr