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Kelleher, John D. (42)
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Hits 1 – 20 of 49
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
. - : arXiv, 2020
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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)
Abstract:
Controllable Image Captioning is a recent sub-field in the multi-modal task of Image Captioning wherein constraints are placed on which regions in an image should be described in the generated natural language caption. This puts a stronger focus on producing more detailed descriptions, and opens the door for more end-user control over results. A vital component of the Controllable Image Captioning architecture is the mechanism that decides the timing of attending to each region through the advancement of a region pointer. In this paper, we propose a novel method for predicting the timing of region pointer advancement by treating the advancement step as a natural part of the language structure via a NEXT-token, motivated by a strong correlation to the sentence structure in the training data. We find that our timing agrees with the ground-truth timing in the Flickr30k Entities test data with a precision of 86.55% and a recall of 97.92%. Our model implementing this technique improves the state-of-the-art on standard captioning metrics while additionally demonstrating a considerably larger effective vocabulary size.
Keyword:
Artificial Intelligence and Robotics
;
computer vision
;
controllable image captioning
;
deep learning
;
machine learning
;
natural language generation
URL:
https://arrow.tudublin.ie/scschcomcon/286
https://arrow.tudublin.ie/cgi/viewcontent.cgi?article=1303&context=scschcomcon
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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
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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12
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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13
TEST: A terminology extraction system for technology related terms
Hossari, Murhaf
;
Dev, Soumyabrata
;
Kelleher, John
In: Conference papers (2019)
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14
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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15
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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16
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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17
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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18
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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19
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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20
Back to the Future: Logic and Machine Learning
Kelleher, John D.
;
Dobnik, Simon
In: Conference papers (2017)
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