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Hits 1 – 20 of 51
1
Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification
Nedumpozhimana, Vasudevan
;
Klubička, Filip
;
Kelleher, John D.
In: Front Artif Intell (2022)
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2
Poisoning Knowledge Graph Embeddings via Relation Inference Patterns ...
Bhardwaj, Peru
;
Kelleher, John
;
Costabello, Luca
. - : arXiv, 2021
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3
Poisoning Knowledge Graph Embeddings via Relation Inference Patterns ...
The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021
;
Bhardwaj, Peru
;
Costabello, Luca
. - : Underline Science Inc., 2021
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4
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods ...
The 2021 Conference on Empirical Methods in Natural Language Processing 2021
;
Bhardwaj, Peru
;
Costabello, Luca
. - : Underline Science Inc., 2021
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5
Style versus Content: A distinction without a (learnable) difference?
Jafaritazehjani, Somayeh
;
Lecorvé, Gwénolé
;
Lolive, Damien
...
In: International Conference on Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-03112354 ; International Conference on Computational Linguistics, Dec 2020, Virtual, Spain (2020)
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6
Language-Driven Region Pointer Advancement for Controllable Image Captioning ...
Lindh, Annika
;
Ross, Robert J.
;
Kelleher, John D.
. - : arXiv, 2020
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7
Semantic Relatedness and Taxonomic Word Embeddings ...
Kacmajor, Magdalena
;
Kelleher, John D.
;
Klubicka, Filip
;
Maldonado, Alfredo
. - : arXiv, 2020
Abstract:
This paper connects a series of papers dealing with taxonomic word embeddings. It begins by noting that there are different types of semantic relatedness and that different lexical representations encode different forms of relatedness. A particularly important distinction within semantic relatedness is that of thematic versus taxonomic relatedness. Next, we present a number of experiments that analyse taxonomic embeddings that have been trained on a synthetic corpus that has been generated via a random walk over a taxonomy. These experiments demonstrate how the properties of the synthetic corpus, such as the percentage of rare words, are affected by the shape of the knowledge graph the corpus is generated from. Finally, we explore the interactions between the relative sizes of natural and synthetic corpora on the performance of embeddings when taxonomic and thematic embeddings are combined. ... : 7 pages 0 figures ...
Keyword:
Artificial Intelligence cs.AI
;
Computation and Language cs.CL
;
FOS Computer and information sciences
;
Machine Learning cs.LG
URL:
https://dx.doi.org/10.48550/arxiv.2002.06235
https://arxiv.org/abs/2002.06235
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8
English WordNet Taxonomic Random Walk Pseudo-Corpora
Klubicka, Filip
;
Maldonado, Alfredo
;
Mahalunkar, Abhijit
...
In: Conference papers (2020)
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9
Language-Driven Region Pointer Advancement for Controllable Image Captioning
Lindh, Annika
;
Ross, Robert
;
Kelleher, John D.
In: Conference papers (2020)
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10
Local Alignment of Frame of Reference Assignment in English and Swedish Dialogue
Dobnik, Simon
;
Kelleher, John D.
;
Howes, Christine
In: Conference papers (2020)
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11
Capturing and measuring thematic relatedness [<Journal>]
Kacmajor, Magdalena Verfasser]
DNB Subject Category Language
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12
Synthetic, Yet Natural: Properties of WordNet Random Walk Corpora and the impact of rare words on embedding performance
Klubicka, Filip
;
Mahalunkar, Abhijit
;
Maldonado, Alfredo
...
In: Conference papers (2019)
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13
Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings
Maldonado, Alfredo
;
Klubicka, Filip
;
Kelleher, John D.
In: Articles (2019)
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14
TEST: A terminology extraction system for technology related terms
Hossari, Murhaf
;
Dev, Soumyabrata
;
Kelleher, John
In: Conference papers (2019)
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15
Modular Mechanistic Networks: On Bridging Mechanistic and Phenomenological Models with Deep Neural Networks in Natural Language Processing ...
Dobnik, Simon
;
Kelleher, John D.
. - : arXiv, 2018
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16
What is not where: the challenge of integrating spatial representations into deep learning architectures ...
Kelleher, John D.
;
Dobnik, Simon
. - : arXiv, 2018
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17
Is it worth it? Budget-related evaluation metrics for model selection ...
Klubička, Filip
;
Salton, Giancarlo D.
;
Kelleher, John D.
. - : arXiv, 2018
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18
Is it worth it? Budget-related evaluation metrics for model selection
Klubicka, Filip
;
Salton, Giancarlo
;
Kelleher, John D.
In: Conference papers (2018)
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19
Exploring the Functional and Geometric Bias of Spatial Relations Using Neural Language Models
Dobnik, Simon
;
Ghanimifard, Mehdi
;
Kelleher, John D.
In: Conference papers (2018)
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20
Idiom Type Identification with Smoothed Lexical Features and a Maximum Margin Classifier ...
Kelleher, John; Ross, Robert J. And Salton, Giancarlo
. - : Dublin Institute of Technology, 2017
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