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1
TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing ...
Gui, Tao; Wang, Xiao; Zhang, Qi. - : arXiv, 2021
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2
SpanNER: Named Entity Re-/Recognition as Span Prediction ...
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3
Align Voting Behavior with Public Statements for Legislator Representation Learning ...
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4
fastHan: A BERT-based Multi-Task Toolkit for Chinese NLP ...
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5
{K-Adapter}: {I}nfusing {K}nowledge into {P}re-{T}rained {M}odels with {A}dapters ...
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6
Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble ...
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7
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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8
Classifying Dyads for Militarized Conflict Analysis
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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9
Efficient Sampling of Dependency Structure
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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10
Searching for More Efficient Dynamic Programs
In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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11
“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding
In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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12
A Bayesian Framework for Information-Theoretic Probing
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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13
Improving Dialogue State Tracking with Turn-based Loss Function and Sequential Data Augmentation
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14
Come hither or go away? Recognising pre-electoral coalition signals in the news
Rehbein, Ines; Ponzetto, Simone Paolo; Adendorf, Anna. - : Association for Computational Linguistics, 2021
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15
K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters ...
Abstract: We study the problem of injecting knowledge into large pre-trained models like BERT and RoBERTa. Existing methods typically update the original parameters of pre-trained models when injecting knowledge. However, when multiple kinds of knowledge are injected, the historically injected knowledge would be flushed away. To address this, we propose K-Adapter, a framework that retains the original parameters of the pre-trained model fixed and supports the development of versatile knowledge-infused model. Taking RoBERTa as the backbone model, K-Adapter has a neural adapter for each kind of infused knowledge, like a plug-in connected to RoBERTa. There is no information flow between different adapters, thus multiple adapters can be efficiently trained in a distributed way. As a case study, we inject two kinds of knowledge in this work, including (1) factual knowledge obtained from automatically aligned text-triplets on Wikipedia and Wikidata and (2) linguistic knowledge obtained via dependency parsing. Results on ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
URL: https://arxiv.org/abs/2002.01808
https://dx.doi.org/10.48550/arxiv.2002.01808
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16
FLAT: Chinese NER Using Flat-Lattice Transformer ...
Li, Xiaonan; Yan, Hang; Qiu, Xipeng. - : arXiv, 2020
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17
A Graph-based Model for Joint Chinese Word Segmentation and Dependency Parsing
In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 78-92 (2020) (2020)
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18
Chinese computational linguistics : 18th China National Conference, CCL 2019, Kunming, China, October 18-20, 2019 : proceedings
Liu, Zhiyuan (Herausgeber); Jiang, Heng (Herausgeber); Liu, Yang (Herausgeber). - Cham, Switzerland : Springer, 2019
BLLDB
UB Frankfurt Linguistik
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19
GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge ...
Huang, Luyao; Sun, Chi; Qiu, Xipeng. - : arXiv, 2019
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20
Distantly Supervised Named Entity Recognition using Positive-Unlabeled Learning ...
Peng, Minlong; Xing, Xiaoyu; Zhang, Qi. - : arXiv, 2019
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