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The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021 (1.255)
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Hits 1.201 – 1.220 of 1.255
1201
Paths to Relation Extraction through Semantic Structure ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
., Omri
;
Yellin, Jonathan
. - : Underline Science Inc., 2021
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1202
Rule Augmented Unsupervised Constituency Parsing ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Iyer, Rishabh
;
Maheshwari, Ayush
. - : Underline Science Inc., 2021
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1203
Transition-based Bubble Parsing: Improvements on Coordination Structure Prediction ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Lee, Lillian
;
Shi, Tianze
. - : Underline Science Inc., 2021
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1204
Dodrio: Exploring Transformer Models with Interactive Visualization ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Chau, Polo
;
Turko, Robert
. - : Underline Science Inc., 2021
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1205
Vyākarana A Colorless Green Benchmark for Syntactic Evaluation in Indic Languages ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Baths, Veeky
;
Dhillon, Jasleen
. - : Underline Science Inc., 2021
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1206
What if This Modified That? Syntactic Interventions with Counterfactual Embeddings ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Levy, Roger
;
Qian, Peng
. - : Underline Science Inc., 2021
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1207
Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Dakota, Daniel
;
Sayyed, Zeeshan
. - : Underline Science Inc., 2021
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1208
The Limitations of Limited Context for Constituency Parsing ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Li, Yuchen
;
Risteski, Andrej
. - : Underline Science Inc., 2021
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1209
Effective Batching for Recurrent Neural Network Grammars ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Noji, Hiroshi
;
Oseki, Yohei
. - : Underline Science Inc., 2021
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1210
Factorising Meaning and Form for Intent-Preserving Paraphrasing ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Hosking, Tom
;
Lapata, Mirella
. - : Underline Science Inc., 2021
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1211
Infusing Finetuning with Semantic Dependencies ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Peng, Hao
;
Smith, Noah
. - : Underline Science Inc., 2021
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1212
7D: Syntax: Tagging, Chunking, and Parsing #1 ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
. - : Underline Science Inc., 2021
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1213
OntoGUM: Evaluating Contextualized SOTA Coreference Resolution on 12 More Genres ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
., Sameer
;
Zeldes, Amir
. - : Underline Science Inc., 2021
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1214
Topicalization in Language Models: A Case Study on Japanese ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Abe, Kaori
;
Fujihara, Riki
. - : Underline Science Inc., 2021
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1215
An In-depth Study on Internal Structure of Chinese Words ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Gong, Chen
;
Huai, Baoxing
. - : Underline Science Inc., 2021
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1216
To Point or Not to Point: Understanding How Abstractive Summarizers Paraphrase Text ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Timkey, William
;
van Schijndel, Marten
. - : Underline Science Inc., 2021
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1217
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
sun, zijun
. - : Underline Science Inc., 2021
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1218
When Do You Need Billions of Words of Pretraining Data? ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
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Bowman, Samuel R.
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Li, Haau-Sing
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Warstadt, Alex
;
Zhang, Yian
. - : Underline Science Inc., 2021
Abstract:
Read paper: https://www.aclanthology.org/2021.acl-long.90 Abstract: NLP is currently dominated by language models like RoBERTa which are pretrained on billions of words. But what exact knowledge or skills do Transformer LMs learn from large-scale pretraining that they cannot learn from less data? To explore this question, we adopt five styles of evaluation: classifier probing, information-theoretic probing, unsupervised relative acceptability judgments, unsupervised language model knowledge probing, and fine-tuning on NLU tasks. We then draw learning curves that track the growth of these different measures of model ability with respect to pretraining data volume using the MiniBERTas, a group of RoBERTa models pretrained on 1M, 10M, 100M and 1B words. We find that these LMs require only about 10M to 100M words to learn to reliably encode most syntactic and semantic features we test. They need a much larger quantity of data in order to acquire enough commonsense knowledge and other skills required to master ...
Keyword:
Computational Linguistics
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Condensed Matter Physics
;
Deep Learning
;
Electromagnetism
;
FOS Physical sciences
;
Information and Knowledge Engineering
;
Neural Network
;
Semantics
URL:
https://underline.io/lecture/25974-when-do-you-need-billions-of-words-of-pretraining-dataquestion
https://dx.doi.org/10.48448/ngkd-rr69
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1219
Bridge-Based Active Domain Adaptation for Aspect Term Extraction ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Chen, Zhuang
. - : Underline Science Inc., 2021
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1220
Recursive Tree-Structured Self-Attention for Answer Sentence Selection ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Farcas, Emilia
;
Mrini, Khalil
. - : Underline Science Inc., 2021
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