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Active Learning by Acquiring Contrastive Examples ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.51/ Abstract: Common acquisition functions for active learning use either uncertainty or diversity sampling, aiming to select difficult and diverse data points from the pool of unlabeled data, respectively. In this work, leveraging the best of both worlds, we propose an acquisition function that opts for selecting contrastive examples, i.e. data points that are similar in the model feature space and yet the model outputs maximally different predictive likelihoods. We compare our approach, CAL (Contrastive Active Learning), with a diverse set of acquisition functions in four natural language understanding tasks and seven datasets. Our experiments show that CAL performs consistently better or equal than the best performing baseline across all tasks, on both in-domain and out-of-domain data. We also conduct an extensive ablation study of our method and we further analyze all actively acquired datasets showing that CAL achieves a better trade-off ...
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Keyword:
Computational Linguistics; Information Extraction; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
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URL: https://underline.io/lecture/37821-active-learning-by-acquiring-contrastive-examples
https://dx.doi.org/10.48448/fh95-3822
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In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering ...
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Machine Translation for the Normalisation of 17th c. French ; Traduction automatique pour la normalisation du français du XVII e siècle
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In: TALN 2020 ; https://hal.archives-ouvertes.fr/hal-02596669 ; TALN 2020, ATALA, Jun 2020, Nancy, France (2020)
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Findings of the 2019 Conference on Machine Translation (WMT19)
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In: Barrault, Loïc orcid:0000-0002-0634-6147 , Bojar, Ondřej orcid:0000-0002-0606-0050 , Costa-Jussà, Marta R. orcid:0000-0002-5703-520X , Federmann, Christian, Fishel, Mark and Graham, Yvette (2019) Findings of the 2019 Conference on Machine Translation (WMT19). In: Fourth Conference on Machine Translation, 1-2 Aug 2019, Florence, Italy. (2019)
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A Workflow For On The Fly Normalisation Of 17th c. French
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In: DH2019 ; https://hal.archives-ouvertes.fr/hal-02276150 ; DH2019, ADHO, Jul 2019, Utrecht, Netherlands (2019)
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What you can cram into a single \$&!#* vector: Probing sentence embeddings for linguistic properties
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In: ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01898412 ; ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Jul 2018, Melbourne, Australia. pp.2126-2136 (2018)
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What you can cram into a single vector: Probing sentence embeddings for linguistic properties ...
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| 10 |
Word Representations in Factored Neural Machine Translation
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In: Proceedings of the Conference on Machine Translation (WMT), ; Conference on Machine Translation ; https://hal.archives-ouvertes.fr/hal-01618384 ; Conference on Machine Translation, Association for Computational Linguistics, Sep 2017, Copenhagen, Denmark. pp.43 - 55 (2017)
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| 11 |
Neural Machine Translation by Generating Multiple Linguistic Factors
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In: 5th International Conference Statistical Language and Speech Processing SLSP 2017 ; https://hal-univ-lemans.archives-ouvertes.fr/hal-01689270 ; 5th International Conference Statistical Language and Speech Processing SLSP 2017, Oct 2017, Le Mans, France. ⟨10.1007/978-3-319-68456-7_2⟩ (2017)
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NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation Systems
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In: ISSN: 1804-0462 ; The Prague Bulletin of Mathematical Linguistics ; https://hal-univ-lemans.archives-ouvertes.fr/hal-01647873 ; The Prague Bulletin of Mathematical Linguistics, Univerzita Karlova v Praze, 2017, 109 (1), ⟨10.1515/pralin-2017-0035⟩ (2017)
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Very Deep Convolutional Networks for Text Classification
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In: European Chapter of the Association for Computational Linguistics EACL'17 ; https://hal.archives-ouvertes.fr/hal-01454940 ; European Chapter of the Association for Computational Linguistics EACL'17, 2017, Valencia, Spain (2017)
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Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description ...
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| 15 |
Neural Machine Translation by Generating Multiple Linguistic Factors ...
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NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation Systems
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In: Prague Bulletin of Mathematical Linguistics , Vol 109, Iss 1, Pp 15-28 (2017) (2017)
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OCR Error Correction Using Statistical Machine Translation
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In: 16th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2015). ; https://hal.archives-ouvertes.fr/hal-01433200 ; 16th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2015)., 2015, Cairo, Egypt (2015)
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Continuous Adaptation to User Feedback for Statistical Machine Translation
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In: North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2015) ; https://hal.archives-ouvertes.fr/hal-01454944 ; North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2015), 2015, Denver (Colorado, USA), Unknown Region (2015)
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