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The 2021 Conference on Empirical Methods in Natural Language Processing 2021 (110)
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Hits 1 – 20 of 110
1
On Homophony and Rényi Entropy ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Cotterell, Ryan
;
Meister, Clara
. - : Underline Science Inc., 2021
BASE
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2
Backtranslation in Neural Morphological Inflection ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Hulden, Mans
;
Liu, Ling
. - : Underline Science Inc., 2021
BASE
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3
Rule-based Morphological Inflection Improves Neural Terminology Translation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Carpuat, Marine
;
Xu, Weijia
. - : Underline Science Inc., 2021
BASE
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4
Translating Headers of Tabular Data: A Pilot Study of Schema Translation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Gao, Yan
;
Guo, Jiaqi
. - : Underline Science Inc., 2021
BASE
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5
An Information-Theoretic Characterization of Morphological Fusion ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Futrell, Richard
;
Hahn, Michael
. - : Underline Science Inc., 2021
BASE
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6
Analyzing the Surprising Variability in Word Embedding Stability Across Languages ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Burdick, Laura
;
Kummerfeld, Jonathan
. - : Underline Science Inc., 2021
BASE
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7
Neural Machine Translation with Heterogeneous Topic Knowledge Embeddings ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Peng, Wei
. - : Underline Science Inc., 2021
BASE
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8
STaCK: Sentence Ordering with Temporal Commonsense Knowledge ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Ghosal, Deepanway
;
Majumder, Navonil
;
Mihalcea, Rada
;
Poria, Soujanya
. - : Underline Science Inc., 2021
Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.683/ Abstract: Sentence order prediction is the task of finding the correct order of sentences in a randomly ordered document. Correctly ordering the sentences requires an understanding of coherence with respect to the chronological sequence of events described in the text. Document-level contextual understanding and commonsense knowledge centered around these events are often essential in uncovering this coherence and predicting the exact chronological order. In this paper, we introduce STaCK—a framework based on graph neural networks and temporal commonsense knowledge to model global information and predict the relative order of sentences. Our graph network accumulates temporal evidence using knowledge of past and future and formulates sentence ordering as a constrained edge classification problem. We report results on five different datasets, and empirically show that the proposed method is naturally suitable for order prediction. The ...
Keyword:
Computational Linguistics
;
Machine Learning
;
Machine Learning and Data Mining
;
Machine translation
;
Natural Language Processing
;
Neural Network
URL:
https://underline.io/lecture/37588-stack-sentence-ordering-with-temporal-commonsense-knowledge
https://dx.doi.org/10.48448/z4ap-sf78
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9
Wikily Supervised Neural Translation Tailored to Cross-Lingual Tasks ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Callison-Burch, Chris
;
Rasooli, Mohammad Sadegh
. - : Underline Science Inc., 2021
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10
Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Gheini, Mozhdeh
;
May, Jonathan
. - : Underline Science Inc., 2021
BASE
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11
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Esplà-Gomis, Miquel
;
Pérez-Ortiz, Juan Antonio
. - : Underline Science Inc., 2021
BASE
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12
Sequence Length is a Domain: Length-based Overfitting in Transformer Models ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Bojar, Ondřej
;
Variš, Dušan
. - : Underline Science Inc., 2021
BASE
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13
Speechformer: Reducing Information Loss in Direct Speech Translation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Gaido, Marco
;
Negri, Matteo
. - : Underline Science Inc., 2021
BASE
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14
Data and Parameter Scaling Laws for Neural Machine Translation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Duh, Kevin
;
Gordon, Mitchell
. - : Underline Science Inc., 2021
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15
A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
De Raedt, Maarten
. - : Underline Science Inc., 2021
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16
Universal Simultaneous Machine Translation with Mixture-of-Experts Wait-k Policy ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Feng, Yang
;
Zhang, Shaolei
. - : Underline Science Inc., 2021
BASE
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17
Learning to Rewrite for Non-Autoregressive Neural Machine Translation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Feng, Xiaocheng
;
Geng, Xinwei
. - : Underline Science Inc., 2021
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18
Towards Making the Most of Dialogue Characteristics for Neural Chat Translation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Fandong
;
Chen, Yufeng
. - : Underline Science Inc., 2021
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19
Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Byrne, Bill
;
Domhan, Tobias
. - : Underline Science Inc., 2021
BASE
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20
Sometimes We Want Ungrammatical Translations ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Parthasarathi, Prasanna
. - : Underline Science Inc., 2021
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