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The 2021 Conference on Empirical Methods in Natural Language Processing 2021 (8)
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Hits 1 – 8 of 8
1
Evaluation of Summarization Systems across Gender, Age, and Race ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Jørgensen, Anna
;
Søgaard, Anders
. - : Underline Science Inc., 2021
BASE
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2
Locke's Holiday: Belief Bias in Machine Reading ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Søgaard, Anders
. - : Underline Science Inc., 2021
BASE
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3
Dynamic Forecasting of Conversation Derailment ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Kementchedjhieva, Yova
;
Søgaard, Anders
. - : Underline Science Inc., 2021
BASE
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4
Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Abdou, Mostafa
;
Frank, Stella
. - : Underline Science Inc., 2021
BASE
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5
A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
de Lhoneux, Miryam
;
Hartmann, Mareike
. - : Underline Science Inc., 2021
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6
Clustering Monolingual Vocabularies to Improve Cross-Lingual Generalization ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Tejaswini
;
Bassani, Riccardo
. - : Underline Science Inc., 2021
BASE
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7
The Impact of Positional Encodings on Multilingual Compression ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Ravishankar, Vinit
;
Søgaard, Anders
. - : Underline Science Inc., 2021
Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.59/ Abstract: In order to preserve word-order information in a non-autoregressive setting, transformer architectures tend to include positional knowledge, by (for instance) adding positional encodings to token embeddings. Several modifications have been proposed over the sinusoidal positional encodings used in the original transformer architecture; these include, for instance, separating position encodings and token embeddings, or directly modifying attention weights based on the distance between word pairs. We first show that surprisingly, while these modifications tend to improve monolingual language models, none of them result in better multilingual language models. We then answer why that is: Sinusoidal encodings were explicitly designed to facilitate compositionality by allowing linear projections over arbitrary time steps. Higher variances in multilingual training distributions requires higher compression, in which case, compositionality ...
Keyword:
Computational Linguistics
;
Language Models
;
Machine Learning
;
Machine Learning and Data Mining
;
Natural Language Processing
URL:
https://underline.io/lecture/37780-the-impact-of-positional-encodings-on-multilingual-compression
https://dx.doi.org/10.48448/gnbq-xb75
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8
On Language Models for Creoles ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
., Miryam
;
Bugliarello, Emanuele
. - : Underline Science Inc., 2021
BASE
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