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Kelleher, John D. (42)
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Hits 1 – 20 of 43
1
Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification
Nedumpozhimana, Vasudevan
;
Klubička, Filip
;
Kelleher, John D.
In: Front Artif Intell (2022)
BASE
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2
Language-Driven Region Pointer Advancement for Controllable Image Captioning ...
Lindh, Annika
;
Ross, Robert J.
;
Kelleher, John D.
. - : arXiv, 2020
BASE
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3
Semantic Relatedness and Taxonomic Word Embeddings ...
Kacmajor, Magdalena
;
Kelleher, John D.
;
Klubicka, Filip
. - : arXiv, 2020
BASE
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4
English WordNet Taxonomic Random Walk Pseudo-Corpora
Klubicka, Filip
;
Maldonado, Alfredo
;
Mahalunkar, Abhijit
...
In: Conference papers (2020)
BASE
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5
Language-Driven Region Pointer Advancement for Controllable Image Captioning
Lindh, Annika
;
Ross, Robert
;
Kelleher, John D.
In: Conference papers (2020)
BASE
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6
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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7
Capturing and measuring thematic relatedness [<Journal>]
Kacmajor, Magdalena Verfasser]
DNB Subject Category Language
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8
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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9
Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings
Maldonado, Alfredo
;
Klubicka, Filip
;
Kelleher, John D.
In: Articles (2019)
BASE
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10
Modular Mechanistic Networks: On Bridging Mechanistic and Phenomenological Models with Deep Neural Networks in Natural Language Processing ...
Dobnik, Simon
;
Kelleher, John D.
. - : arXiv, 2018
BASE
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11
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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12
Is it worth it? Budget-related evaluation metrics for model selection ...
Klubička, Filip
;
Salton, Giancarlo D.
;
Kelleher, John D.
. - : arXiv, 2018
Abstract:
Creating a linguistic resource is often done by using a machine learning model that filters the content that goes through to a human annotator, before going into the final resource. However, budgets are often limited, and the amount of available data exceeds the amount of affordable annotation. In order to optimize the benefit from the invested human work, we argue that deciding on which model one should employ depends not only on generalized evaluation metrics such as F-score, but also on the gain metric. Because the model with the highest F-score may not necessarily have the best sequencing of predicted classes, this may lead to wasting funds on annotating false positives, yielding zero improvement of the linguistic resource. We exemplify our point with a case study, using real data from a task of building a verb-noun idiom dictionary. We show that, given the choice of three systems with varying F-scores, the system with the highest F-score does not yield the highest profits. In other words, in our case ... : 7 pages, 1 figure, 5 tables, In proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ...
Keyword:
Computation and Language cs.CL
;
FOS Computer and information sciences
URL:
https://arxiv.org/abs/1807.06998
https://dx.doi.org/10.48550/arxiv.1807.06998
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13
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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14
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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15
Back to the Future: Logic and Machine Learning
Kelleher, John D.
;
Dobnik, Simon
In: Conference papers (2017)
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16
Robot Perception Errors and Human Resolution Strategies in Situated Human-Robot Dialogue
Kelleher, John D.
;
Mac Namee, Brian
;
Schütte, Niels
In: Articles (2017)
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17
Assessing the Usefulness of Different Feature Sets for Predicting the Comprehension Difficulty of Text
Mac Namee, Brian
;
Kelleher, John D.
;
Fitzpatrick, Noel
In: Conference papers (2017)
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18
Towards a Computational Model of Frame of Reference Alignment in Swedish Dialogue
Dobnik, Simon
;
Howes, Christine
;
Kelleher, John D.
...
In: Conference papers (2016)
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19
A Model for Attention-Driven Judgements in Type Theory with Records
Dobnik, Simon
;
Kelleher, John D.
In: Conference papers (2016)
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20
Fundamentals of Machine Learning for Neural Machine Translation
Kelleher, John D.
In: Conference papers (2016)
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