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Simple Search
Hits 1 – 6 of 6
1
Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehension ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Harsh
;
Balasubramanian, Niranjan
. - : Underline Science Inc., 2021
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2
SHAPE: Shifted Absolute Position Embedding for Transformers ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Inui, Kentaro
;
Kiyono, Shun
. - : Underline Science Inc., 2021
BASE
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3
Incorporating Residual and Normalization Layers into Analysis of Masked Language Models ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Inui, Kentaro
;
Kobayashi, Goro
. - : Underline Science Inc., 2021
BASE
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4
Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Inui, Kentaro
;
Kiyono, Shun
. - : Underline Science Inc., 2021
BASE
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5
Exploring Methods for Generating Feedback Comments for Writing Learning ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Hanawa, Kazuaki
;
Inui, Kentaro
;
Nagata, Ryo
. - : Underline Science Inc., 2021
Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.766/ Abstract: The task of generating explanatory notes for language learners is known as feedback comment generation. Although various generation techniques are available, little is known about which methods are appropriate for this task. Nagata (2019) demonstrates the effectiveness of neural-retrieval-based methods in generating feedback comments for preposition use. Retrieval-based methods have limitations in that they can only output feedback comments existing in a given training data. Furthermore, feedback comments can be made on other grammatical and writing items than preposition use, which is still unaddressed. To shed light on these points, we investigate a wider range of methods for generating many feedback comments in this study. Our close analysis of the type of task leads us to investigate three different architectures for comment generation: (i) a neural-retrieval-based method as a baseline, (ii) a pointer-generator-based generation ...
Keyword:
Computational Linguistics
;
Machine Learning
;
Machine Learning and Data Mining
;
Natural Language Processing
URL:
https://underline.io/lecture/38057-exploring-methods-for-generating-feedback-comments-for-writing-learning
https://dx.doi.org/10.48448/7wnw-3s42
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6
Transformer-based Lexically Constrained Headline Generation ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Hitomi, Yuta
;
Inui, Kentaro
. - : Underline Science Inc., 2021
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