scholar.google.com › citations
Nov 27, 2023 · A deep learning-based few-shot NER model was designed to improve the recognition effect of named entities in marine ecology.
For the proposed few-shot NER method based on deep learning, comparative experiments were conducted horizontally and vertically against BiLSTM-CRF, IDCNN-CRF, ...
Aug 1, 2021 · In this paper, we present a human-annotated dataset, FEW-NERD, for few-shot learning in. NER. We describe the details of the collection pro-.
Missing: Ecology | Show results with:Ecology
Nov 11, 2021 · This paper presents an empirical study to effi- ciently build named entity recognition (NER) systems when a small amount of in-domain.
Missing: Marine Ecology
Aug 17, 2023 · A multi-task-based few-shot named entity recognition model (FSPD-NER) for power dispatch is proposed. The model consists of four modules.
Dec 9, 2024 · This paper presents a Chinese word segmentation system that uses improved source-channel models of Chinese sentence generation. Chinese words ...
Mar 27, 2022 · Few-shot NER is the task of making work named entity recognition (NER) systems when a small number of in-domain labeled data is available. In ...
Apr 28, 2023 · We propose a decomposed prompt learning NER framework for few-shot settings, decomposing the NER task into two stages: entity locating and entity typing.
Sep 29, 2021 · We provide insight into popular deep learning approaches for ecological data analysis in plain language, focusing on the techniques of ...
Missing: NER | Show results with:NER
Jun 6, 2024 · We conclude that few-shot prompting on LLMs has abysmal performance, whereas the fine-tuned spaCy-transformer emerges as the best model with ...
Missing: Marine | Show results with:Marine