arXiv:1701.01623
공식 코드 · Papers with Code
Cross-Lingual Dependency Parsing with Late Decoding for Truly Low-Resource Languages
원문 초록
In cross-lingual dependency annotation projection, information is often lost during transfer because of early decoding. We present an end-to-end graph-based neural network dependency parser that can be trained to reproduce matrices of edge scores, which can be directly projected across word alignments. We show that our approach to cross-lingual dependency parsing is not only simpler, but also achieves an absolute improvement of 2.25% averaged across 10 languages compared to the previous state of the art.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Step-by-step Instructions and a Simple Tabular Output Format Improve the Dependency Parsing Accuracy of LLMs
Hierarchical Bracketing Encodings for Dependency Parsing as Tagging
An Aspect Extraction Framework using Different Embedding Types, Learning Models, and Dependency Structure
Multi-View Attention Syntactic Enhanced Graph Convolutional Network for Aspect-based Sentiment Analysis
Top General Performance = Top Domain Performance? DomainCodeBench: A Multi-domain Code Generation Benchmark
Error Diversity Matters: An Error-Resistant Ensemble Method for Unsupervised Dependency Parsing
토론
이 논문과 연결된 포럼 글이 아직 없습니다.