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The 2021 Conference on Empirical Methods in Natural Language Processing 2021 (1.029)
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2021 (1.029)
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Hits 21 – 40 of 1.029
21
A Prototype Free/Open-Source Morphological Analyser and Generator for Sakha ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Jonathan
;
Ivanova, Sardana
. - : Underline Science Inc., 2021
BASE
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22
Automatic Error Type Annotation for Arabic ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Belkebir, Riadh
;
Habash, Nizar
. - : Underline Science Inc., 2021
BASE
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23
Developing Conversational Data and Detection of Conversational Humor in Telugu ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Pétur O.
;
Jónsson, Haukur P.
. - : Underline Science Inc., 2021
BASE
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24
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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25
Cross-document Event Identity via Dense Annotation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Hasegawa, Kimihiro
;
Li, Linwei
. - : Underline Science Inc., 2021
BASE
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26
Navigating the Kaleidoscope of COVID-19 Misinformation Using Deep Learning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Chen, Yuanzhi
;
Hasan, Mohammad
. - : Underline Science Inc., 2021
BASE
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27
(Mis)alignment Between Stance Expressed in Social Media Data and Public Opinion Surveys ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Shugars, Sarah
. - : Underline Science Inc., 2021
BASE
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28
Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Zuo, Simiao
. - : Underline Science Inc., 2021
BASE
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29
Rewards with Negative Examples for Reinforced Topic-Focused Abstractive Summarization ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Markus
;
Liu, Can
. - : Underline Science Inc., 2021
BASE
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30
Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Han, Jiawei
;
Huang, Jiaxin
. - : Underline Science Inc., 2021
BASE
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31
Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source Pretraining ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Zou, Yicheng
. - : Underline Science Inc., 2021
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32
HittER: Hierarchical Transformers for Knowledge Graph Embeddings ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Chen, Sanxing
;
Gao, Jianfeng
. - : Underline Science Inc., 2021
BASE
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33
Ara-Women-Hate: The first Arabic Hate Speech corpus regarding Women ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Guellil, Imane
. - : Underline Science Inc., 2021
BASE
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34
Detecting Gender Bias using Explainability ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Krithika
;
Gupta, Gauri
. - : Underline Science Inc., 2021
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35
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
He, Lifang
;
LIU, YE
;
S. Yu, Philip
;
Wan, Yao
;
Xia, Congying
;
Zhang, Jianguo
. - : Underline Science Inc., 2021
Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.13/ Abstract: To capture the semantic graph structure from raw text, most existing summarization approaches are built on GNNs with a pre-trained model. However, these methods suffer from cumbersome procedures and inefficient computations for long-text documents. To mitigate these issues, this paper proposes HETFORMER, a Transformer-based pre-trained model with multi-granularity sparse attentions for long-text extractive summarization. Specifically, we model different types of semantic nodes in raw text as a potential heterogeneous graph and directly learn heterogeneous relationships (edges) among nodes by Transformer. Extensive experiments on both single- and multi-document summarization tasks show that HETFORMER achieves state-of-the-art performance in Rouge F1 while using less memory and fewer parameters. ...
Keyword:
Computational Linguistics
;
Language Models
;
Machine Learning
;
Machine Learning and Data Mining
;
Natural Language Processing
;
Text Summarization
URL:
https://underline.io/lecture/37574-hetformer-heterogeneous-transformer-with-sparse-attention-for-long-text-extractive-summarization
https://dx.doi.org/10.48448/za5a-2696
BASE
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36
Blindness to Modality Helps Entailment Graph Mining ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Mark
;
Bijl de Vroe, Sander
. - : Underline Science Inc., 2021
BASE
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37
Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Liu, Ruixuan
;
Sun, Guangzhong
. - : Underline Science Inc., 2021
BASE
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38
Characterizing Test Anxiety on Social Media ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Julka, Esha
;
Kowalishin, Olivia
. - : Underline Science Inc., 2021
BASE
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39
Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Ong, Desmond
;
Suresh, Varsha
. - : Underline Science Inc., 2021
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40
Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Lai, Shaopeng
. - : Underline Science Inc., 2021
BASE
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