DE eng

Search in the Catalogues and Directories

Page: 1...46 47 48 49 50 51 52
Hits 981 – 1.000 of 1.029

981
Linking learning to language typology ...
BASE
Show details
982
Vyākarana: A Colorless Green Benchmark for Syntactic Evaluation in Indic Languages ...
BASE
Show details
983
A Corpus-based Syntactic Analysis of Two-termed Unlike Coordination ...
BASE
Show details
984
A Fine-grained Annotated Corpus for Target-Based Opinion Analysis in Economy - Finance ...
BASE
Show details
985
Shaking Syntactic Trees on the Sesame Street: Multilingual Probing with Controllable Perturbations ...
BASE
Show details
986
On the Relation between Syntactic Divergence and Zero-Shot Performance ...
BASE
Show details
987
Discovering Representation Sprachbund For Multilingual Pre-Training ...
BASE
Show details
988
AESOP: Paraphrase Generation with Adaptive Syntactic Control ...
Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.420/ Abstract: We propose to control paraphrase generation with carefully chosen target syntactic structures to generate more proper and higher-quality paraphrases. Our model, AESOP, leverages a pretrained language model and purposefully selected syntactical control via a retrieval-based selection module to generate fluent paraphrases. Experiments show that AESOP achieves state-of-the-art performances on semantic preservation and syntactic conformation on two benchmark datasets with ground-truth syntactic control from human-annotated exemplars. Moreover, with the retrieval-based target syntax selection module, AESOP generates paraphrases with even better qualities than the current best model using human-annotated target syntactic parses according to human evaluation. We further demonstrate the effectiveness of AESOP to improve classification models' robustness to syntactic perturbation by data augmentation on two GLUE tasks. ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
URL: https://underline.io/lecture/37911-aesop-paraphrase-generation-with-adaptive-syntactic-control
https://dx.doi.org/10.48448/4d09-em33
BASE
Hide details
989
Anatomy of OntoGUM---Adapting GUM to the OntoNotes Scheme to Evaluate Robustness of SOTA Coreference Algorithms ...
BASE
Show details
990
Joint Universal Syntactic and Semantic Parsing ...
BASE
Show details
991
Exploring the Role of BERT Token Representations to Explain Sentence Probing Results ...
BASE
Show details
992
Discovering Representation Sprachbund For Multilingual Pre-Training ...
BASE
Show details
993
Syntax Role for Neural Semantic Role Labeling ...
BASE
Show details
994
How much pretraining data do language models need to learn syntax? ...
BASE
Show details
995
Probing Pre-trained Language Models for Semantic Attributes and their Values ...
BASE
Show details
996
Unsupervised Chunking as Syntactic Structure Induction with a Knowledge-Transfer Approach ...
BASE
Show details
997
Powering Comparative Classification with Sentiment Analysis via Domain Adaptive Knowledge Transfer ...
BASE
Show details
998
Improving Text Generation via Neural Discourse Planning ...
BASE
Show details
999
The Language Model Understood the Prompt was Ambiguous: Probing Syntactic Uncertainty Through Generation ...
BASE
Show details
1000
Test Harder than You Train: Probing with Extrapolation Splits ...
BASE
Show details

Page: 1...46 47 48 49 50 51 52

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
1.029
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern