arXiv:1906.10002
공식 코드 · Papers with Code
LIAAD at SemDeep-5 Challenge: Word-in-Context (WiC)
원문 초록
This paper describes the LIAAD system that was ranked second place in the Word-in-Context challenge (WiC) featured in SemDeep-5. Our solution is based on a novel system for Word Sense Disambiguation (WSD) using contextual embeddings and full-inventory sense embeddings. We adapt this WSD system, in a straightforward manner, for the present task of detecting whether the same sense occurs in a pair of sentences. Additionally, we show that our solution is able to achieve competitive performance even without using the provided training or development sets, mitigating potential concerns related to task overfitting
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
SANDWiCH: Semantical Analysis of Neighbours for Disambiguating Words in Context ad Hoc
Fietje: An open, efficient LLM for Dutch
LexMatcher: Dictionary-centric Data Collection for LLM-based Machine Translation
Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses?
3AM: An Ambiguity-Aware Multi-Modal Machine Translation Dataset
PejorativITy: Disambiguating Pejorative Epithets to Improve Misogyny Detection in Italian Tweets
토론
이 논문과 연결된 포럼 글이 아직 없습니다.