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The 2021 Conference on Empirical Methods in Natural Language Processing 2021 (6)
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., Harsh (1)
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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
;
Kuribayashi, Tatsuki
;
Yokoi, Sho
. - : Underline Science Inc., 2021
Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.373/ Abstract: Transformer architecture has become ubiquitous in the natural language processing field. To interpret the Transformer-based models, their attention patterns have been extensively analyzed. However, the Transformer architecture is not only composed of the multi-head attention; other components can also contribute to Transformers’ progressive performance. In this study, we extended the scope of the analysis of Transformers from solely the attention patterns to the whole attention block, i.e., multi-head attention, residual connection, and layer normalization. Our analysis of Transformer-based masked language models shows that the token-to-token interaction performed via attention has less impact on the intermediate representations than previously assumed. These results provide new intuitive explanations of existing reports; for example, discarding the learned attention patterns tends not to adversely affect the performance. The codes ...
Keyword:
Computational Linguistics
;
Language Models
;
Machine Learning
;
Machine Learning and Data Mining
;
Natural Language Processing
URL:
https://dx.doi.org/10.48448/jh7m-qw81
https://underline.io/lecture/38024-incorporating-residual-and-normalization-layers-into-analysis-of-masked-language-models
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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
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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
. - : Underline Science Inc., 2021
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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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