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1
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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2
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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3
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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4
Enhancing Cognitive Models of Emotions with Representation Learning ...
Guo, Yuting; Choi, Jinho. - : arXiv, 2021
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5
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation ...
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6
Intensionalizing Abstract Meaning Representations: Non-Veridicality and Scope ...
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7
The Stem Cell Hypothesis: Dilemma behind Multi-Task Learning with Transformer Encoders ...
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8
Levi Graph AMR Parser using Heterogeneous Attention ...
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9
Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency Graph ...
Xu, Liyan; Zhang, Xuchao; Zong, Bo. - : arXiv, 2021
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10
Universal Dependencies 2.7
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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11
Universal Dependencies 2.6
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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12
Transformers to Learn Hierarchical Contexts in Multiparty Dialogue for Span-based Question Answering ...
Li, Changmao; Choi, Jinho D.. - : arXiv, 2020
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13
Universal Dependencies 2.5
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019
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14
Universal Dependencies 2.4
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019
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15
Automatic Text-based Personality Recognition on Monologues and Multiparty Dialogues Using Attentive Networks and Contextual Embeddings ...
Abstract: Previous works related to automatic personality recognition focus on using traditional classification models with linguistic features. However, attentive neural networks with contextual embeddings, which have achieved huge success in text classification, are rarely explored for this task. In this project, we have two major contributions. First, we create the first dialogue-based personality dataset, FriendsPersona, by annotating 5 personality traits of speakers from Friends TV Show through crowdsourcing. Second, we present a novel approach to automatic personality recognition using pre-trained contextual embeddings (BERT and RoBERTa) and attentive neural networks. Our models largely improve the state-of-art results on the monologue Essays dataset by 2.49%, and establish a solid benchmark on our FriendsPersona. By comparing results in two datasets, we demonstrate the challenges of modeling personality in multi-party dialogue. ... : Paper Accepted to AAAI-20 Student Abstract and Poster Program ...
Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1911.09304
https://arxiv.org/abs/1911.09304
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16
Universal Dependencies 2.2
In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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17
Universal Dependencies 2.3
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018
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18
Universal Dependencies 2.2
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018
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19
Do FreeWord Order Languages Need More Treebank Data? Investigating Dative Alternation in German, English, and Russian
Gilmanov, Timur [Verfasser]; Abo Mokh, Noor [Verfasser]; Kim, Evgeny [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
DNB Subject Category Language
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20
Universal Dependencies 2.1
In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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