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Hits 41 – 60 of 135

41
An exploratory study on multilingual quality estimation
In: 366 ; 377 (2020)
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42
Multimodal quality estimation for machine translation
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics ; 1233 ; 1240 (2020)
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43
BERGAMOT-LATTE submissions for the WMT20 quality estimation shared task
In: 1010 ; 1017 (2020)
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44
Findings of the WMT 2020 shared task on quality estimation
In: 743 ; 764 (2020)
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45
MLQE-PE: A multilingual quality estimation and post-editing dataset
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46
Data-Driven Sentence Simplification: Survey and Benchmark
In: Computational Linguistics, Vol 46, Iss 1, Pp 135-187 (2020) (2020)
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47
Common20LS: A Lexical Simplification Dataset with Demographic Information ...
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48
Common20LS: A Lexical Simplification Dataset with Demographic Information ...
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49
Taking MT Evaluation Metrics to Extremes: Beyond Correlation with Human Judgments
In: Computational Linguistics, Vol 45, Iss 3, Pp 515-558 (2019) (2019)
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50
WMT18 Quality Estimation Shared Task Test Data
Specia, Lucia; Logacheva, Varvara; Blain, Frederic. - : University of Sheffield, 2018
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51
WMT18 Quality Estimation Shared Task Training and Development Data
Specia, Lucia; Logacheva, Varvara; Blain, Frederic. - : University of Sheffield, 2018
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52
A Report on the Complex Word Identification Shared Task 2018 ...
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53
Assessing Crosslingual Discourse Relations in Machine Translation ...
Smith, Karin Sim; Specia, Lucia. - : arXiv, 2018
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54
End-to-end Image Captioning Exploits Multimodal Distributional Similarity ...
Abstract: We hypothesize that end-to-end neural image captioning systems work seemingly well because they exploit and learn `distributional similarity' in a multimodal feature space by mapping a test image to similar training images in this space and generating a caption from the same space. To validate our hypothesis, we focus on the `image' side of image captioning, and vary the input image representation but keep the RNN text generation component of a CNN-RNN model constant. Our analysis indicates that image captioning models (i) are capable of separating structure from noisy input representations; (ii) suffer virtually no significant performance loss when a high dimensional representation is compressed to a lower dimensional space; (iii) cluster images with similar visual and linguistic information together. Our findings indicate that our distributional similarity hypothesis holds. We conclude that regardless of the image representation used image captioning systems seem to match images and generate captions in a ... : Published in BMVC 2018 ...
Keyword: Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1809.04144
https://arxiv.org/abs/1809.04144
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55
Defoiling Foiled Image Captions ...
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56
Object Counts! Bringing Explicit Detections Back into Image Captioning ...
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57
Text Simplification From Professionally Produced Corpora ...
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58
SimPA: A Sentence-Level Simplification Corpus for the Public Administration Domain ...
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59
SimPA: A Sentence-Level Simplification Corpus for the Public Administration Domain ...
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60
Text Simplification From Professionally Produced Corpora ...
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