Doc2FRC: Length-Consistent Document-Level Machine Translation via Fixed-Range Chunking

Excerpt

arXiv:2609.12674v1 Announce Type: new Abstract: Advanced large language models (LLMs) with long context windows can substantially reduce input truncation in document-level machine translation (DocMT). However, direct Doc2Doc translation remains prone to n-gram repetition and progressive quality degradation. A common remedy is to segment the document into finer-grained chunks. Nonetheless, conventional rule-based chunking approaches fail to handle the length distribution mismatch between training