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1
Pushing the right buttons: adversarial evaluation of quality estimation
In: Proceedings of the Sixth Conference on Machine Translation ; 625 ; 638 (2022)
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2
Translation Error Detection as Rationale Extraction ...
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3
Knowledge Distillation for Quality Estimation ...
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4
BERTGEN: Multi-task Generation through BERT ...
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5
Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications ...
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6
A Generative Framework for Simultaneous Machine Translation ...
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Continual Quality Estimation with Online Bayesian Meta-Learning ...
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8
SentSim: Crosslingual Semantic Evaluation of Machine Translation ...
NAACL 2021 2021; Song, Yurun; Specia, Lucia. - : Underline Science Inc., 2021
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9
Knowledge Distillation for Quality Estimation ...
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10
BERTGen: Multi-task Generation through BERT ...
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11
What Makes a Scientific Paper be Accepted for Publication? ...
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12
MultiSubs: A Large-scale Multimodal and Multilingual Dataset ...
Abstract: This paper introduces a large-scale multimodal and multilingual dataset that aims to facilitate research on grounding words to images in their contextual usage in language. The dataset consists of images selected to unambiguously illustrate concepts expressed in sentences from movie subtitles. The dataset is a valuable resource as (i) the images are aligned to text fragments rather than whole sentences; (ii) multiple images are possible for a text fragment and a sentence; (iii) the sentences are free-form and real-world like; (iv) the parallel texts are multilingual. We set up a fill-in-the-blank game for humans to evaluate the quality of the automatic image selection process of our dataset. We show the utility of the dataset on two automatic tasks: (i) fill-in-the blank; (ii) lexical translation. Results of the human evaluation and automatic models demonstrate that images can be a useful complement to the textual context. The dataset will benefit research on visual grounding of words especially in the ... : Manuscript update: (i) Added links to the dataset and evaluation toolkit; (ii) Section 6.1.4: Added random and n-gram baselines to the fill-in-the-blank task, and added further discussion at the end of the section; (iii) Section 6.2.3: Further elaboration on the ALI metric; (iv) Section 6.2.4: Corrected results for the lexical translation task (Table 8), and updated the discussions accordingly ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2103.01910
https://dx.doi.org/10.48550/arxiv.2103.01910
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13
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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14
Classifying Dyads for Militarized Conflict Analysis
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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15
Efficient Sampling of Dependency Structure
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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16
Searching for More Efficient Dynamic Programs
In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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17
“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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18
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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19
Findings of the WMT 2021 Shared Task on Quality Estimation ...
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20
Pushing the Right Buttons: Adversarial Evaluation of Quality Estimation ...
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