DE eng

Search in the Catalogues and Directories

Page: 1 2 3 4 5 6 7...47
Hits 41 – 60 of 922

41
SUBSUME: A Dataset for Subjective Summary Extraction from Wikipedia Documents ...
BASE
Show details
42
Few-Shot Named Entity Recognition: An Empirical Baseline Study ...
BASE
Show details
43
Low-resource Taxonomy Enrichment with Pretrained Language Models ...
BASE
Show details
44
Knowing False Negatives: An Adversarial Training Method for Distantly Supervised Relation Extraction ...
BASE
Show details
45
Extend, donÕt rebuild: Phrasing conditional graph modification as autoregressive sequence labelling ...
BASE
Show details
46
Treasures Outside Contexts: Improving Event Detection via Global Statistics ...
BASE
Show details
47
Cost-effective End-to-end Information Extraction for Semi-structured Document Images ...
BASE
Show details
48
Monitoring geometrical properties of word embeddings for detecting the emergence of new topics. ...
BASE
Show details
49
Coarse2Fine: Fine-grained Text Classification on Coarsely-grained Annotated Data ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.46/ Abstract: Existing text classification methods mainly focus on a fixed label set, whereas many real-world applications require extending to new fine-grained classes as the number of samples per label increases. To accommodate such requirements, we introduce a new problem called coarse-to-fine grained classification, which aims to perform fine-grained classification on coarsely annotated data. Instead of asking for new fine-grained human annotations, we opt to leverage label surface names as the only human guidance and weave in rich pre-trained generative language models into the iterative weak supervision strategy. Specifically, we first propose a label-conditioned finetuning formulation to attune these generators for our task. Furthermore, we devise a regularization objective based on the coarse-fine label constraints derived from our problem setting, giving us even further improvements over the prior formulation. Our framework uses the ...
Keyword: Computational Linguistics; Information Extraction; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://underline.io/lecture/37593-coarse2fine-fine-grained-text-classification-on-coarsely-grained-annotated-data
https://dx.doi.org/10.48448/fwwd-tm26
BASE
Hide details
50
Robust Retrieval Augmented Generation for Zero-shot Slot Filling ...
BASE
Show details
51
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation ...
BASE
Show details
52
Structure-Augmented Keyphrase Generation ...
BASE
Show details
53
Document-level Entity-based Extraction as Template Generation ...
BASE
Show details
54
TEBNER: Domain Specific Named Entity Recognition with Type Expanded Boundary-aware Network ...
BASE
Show details
55
Synchronous Dual Network with Cross-Type Attention for Joint Entity and Relation Extraction ...
BASE
Show details
56
Data Augmentation for Cross-Domain Named Entity Recognition ...
BASE
Show details
57
Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction ...
BASE
Show details
58
Joint Multi-modal Aspect-Sentiment Analysis with Auxiliary Cross-modal Relation Detection ...
BASE
Show details
59
Active Learning by Acquiring Contrastive Examples ...
BASE
Show details
60
A Bag of Tricks for Dialogue Summarization ...
BASE
Show details

Page: 1 2 3 4 5 6 7...47

Catalogues
27
5
0
0
0
0
2
Bibliographies
10
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
887
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern