반응형 오늘의 자연어 처리572 [2022-12-18] 오늘의 자연어처리 TRIP: Triangular Document-level Pre-training for Multilingual Language Models Despite the current success of multilingual pre-training, most prior works focus on leveraging monolingual data or bilingual parallel data and overlooked the value of trilingual parallel data. This paper presents \textbf{Tri}angular Document-level \textbf{P}re-training (\textbf{TRIP}), which is the first in the field t.. 2022. 12. 18. [2022-12-18] 오늘의 자연어처리 Using Natural Language Processing to Predict Costume Core Vocabulary of Historical Artifacts Historic dress artifacts are a valuable source for human studies. In particular, they can provide important insights into the social aspects of their corresponding era. These insights are commonly drawn from garment pictures as well as the accompanying descriptions and are usually stored in a standardize.. 2022. 12. 18. [2022-12-17] 오늘의 자연어처리 Using Natural Language Processing to Predict Costume Core Vocabulary of Historical Artifacts Historic dress artifacts are a valuable source for human studies. In particular, they can provide important insights into the social aspects of their corresponding era. These insights are commonly drawn from garment pictures as well as the accompanying descriptions and are usually stored in a standardize.. 2022. 12. 17. [2022-12-16] 오늘의 자연어처리 DialogQAE: N-to-N Question Answer Pair Extraction from Customer Service Chatlog Harvesting question-answer (QA) pairs from customer service chatlog in the wild is an efficient way to enrich the knowledge base for customer service chatbots in the cold start or continuous integration scenarios. Prior work attempts to obtain 1-to-1 QA pairs from growing customer service chatlog, which fails to inte.. 2022. 12. 16. 이전 1 ··· 99 100 101 102 103 104 105 ··· 143 다음 반응형