Improving cross-lingual model transfer by chunking
We present a shallow parser guided cross-lingual model transfer approach in order to address the syntactic differences between source and target languages more effectively. In this work, we assume the chunks or phrases in a sentence as transfer units in order to address the syntactic differences between the source and target languages arising due to the differences in ordering of words in the phrases and the ordering of phrases in a sentence separately.
Code (0)
등록된 구현이 없습니다.
Tasks
ChunkingmodelSentenceSimilar Papers 제목 키워드 기반
Cross-lingual transfer parser from Hindi to Bengali using delexicalization and chunking
Development of a Bengali parser by cross-lingual transfer from Hindi
In recent years there has been a lot of interest in cross-lingual parsing for developing treebanks for languages with small or no annotated treebanks. In this paper, we explore the development of a cross-lingual transfer…
ChunkingCross-Lingual TransferSentenceSEEK: Semantic Evidence Extraction via Adaptive ChunKing for Multilingual Fact-Checking
Multilingual fact verification requires evidence that is both relevant and sufficiently complete for reliable factuality prediction. However, existing systems often rely on search snippets, sentence-level evidence, or lo…
Fact VerificationBenchmarking Google Embeddings 2 against Open-Source Models for Multilingual Dense Retrieval and RAG Systems
We benchmark Google Embeddings (GE2), a Vertex-AI-hosted bi-encoder with 2,048-token context and explicit task-type conditioning, against five open-source alternatives: BGE-M3, E5-large, Multilingual-E5-large (mE5-L), La…
Multi-Task Cross-Lingual Sequence Tagging from Scratch
We present a deep hierarchical recurrent neural network for sequence tagging. Given a sequence of words, our model employs deep gated recurrent units on both character and word levels to encode morphology and context inf…
ChunkingFeature EngineeringNERPOS+1