DE eng

Search in the Catalogues and Directories

Page: 1 2 3 4 5 6 7 8 9...690
Hits 81 – 100 of 13.783

81
Adapting BigScience Multilingual Model to Unseen Languages ...
BASE
Show details
82
On Efficiently Acquiring Annotations for Multilingual Models ...
BASE
Show details
83
Team ÚFAL at CMCL 2022 Shared Task: Figuring out the correct recipe for predicting Eye-Tracking features using Pretrained Language Models ...
BASE
Show details
84
Does Corpus Quality Really Matter for Low-Resource Languages? ...
BASE
Show details
85
IIITDWD-ShankarB@ Dravidian-CodeMixi-HASOC2021: mBERT based model for identification of offensive content in south Indian languages ...
Biradar, Shankar; Saumya, Sunil. - : arXiv, 2022
BASE
Show details
86
mSLAM: Massively multilingual joint pre-training for speech and text ...
Bapna, Ankur; Cherry, Colin; Zhang, Yu. - : arXiv, 2022
BASE
Show details
87
On the Representation Collapse of Sparse Mixture of Experts ...
Chi, Zewen; Dong, Li; Huang, Shaohan. - : arXiv, 2022
BASE
Show details
88
Politics and Virality in the Time of Twitter: A Large-Scale Cross-Party Sentiment Analysis in Greece, Spain and United Kingdom ...
BASE
Show details
89
L3Cube-MahaHate: A Tweet-based Marathi Hate Speech Detection Dataset and BERT models ...
BASE
Show details
90
Few-Shot Cross-lingual Transfer for Coarse-grained De-identification of Code-Mixed Clinical Texts ...
BASE
Show details
91
A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model ...
Abstract: Synthetic data construction of Grammatical Error Correction (GEC) for non-English languages relies heavily on human-designed and language-specific rules, which produce limited error-corrected patterns. In this paper, we propose a generic and language-independent strategy for multilingual GEC, which can train a GEC system effectively for a new non-English language with only two easy-to-access resources: 1) a pretrained cross-lingual language model (PXLM) and 2) parallel translation data between English and the language. Our approach creates diverse parallel GEC data without any language-specific operations by taking the non-autoregressive translation generated by PXLM and the gold translation as error-corrected sentence pairs. Then, we reuse PXLM to initialize the GEC model and pretrain it with the synthetic data generated by itself, which yields further improvement. We evaluate our approach on three public benchmarks of GEC in different languages. It achieves the state-of-the-art results on the NLPCC 2018 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
URL: https://dx.doi.org/10.48550/arxiv.2201.10707
https://arxiv.org/abs/2201.10707
BASE
Hide details
92
A New Generation of Perspective API: Efficient Multilingual Character-level Transformers ...
Lees, Alyssa; Tran, Vinh Q.; Tay, Yi. - : arXiv, 2022
BASE
Show details
93
Factual Consistency of Multilingual Pretrained Language Models ...
BASE
Show details
94
Examining Scaling and Transfer of Language Model Architectures for Machine Translation ...
BASE
Show details
95
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset ...
BASE
Show details
96
Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi ...
BASE
Show details
97
Agreement ...
Tal, Shira. - : Open Science Framework, 2022
BASE
Show details
98
Agreement ...
Tal, Shira. - : Open Science Framework, 2022
BASE
Show details
99
Natural Language Descriptions of Deep Visual Features ...
BASE
Show details
100
From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction ...
BASE
Show details

Page: 1 2 3 4 5 6 7 8 9...690

Catalogues
517
4
412
0
2
0
22
Bibliographies
2.117
0
0
0
0
0
0
5
50
Linked Open Data catalogues
0
Online resources
73
17
0
0
Open access documents
11.476
5
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern