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1
Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification
In: Front Artif Intell (2022)
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2
Language-Driven Region Pointer Advancement for Controllable Image Captioning ...
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3
Semantic Relatedness and Taxonomic Word Embeddings ...
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4
English WordNet Taxonomic Random Walk Pseudo-Corpora
In: Conference papers (2020)
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5
Language-Driven Region Pointer Advancement for Controllable Image Captioning
In: Conference papers (2020)
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6
Local Alignment of Frame of Reference Assignment in English and Swedish Dialogue
In: Conference papers (2020)
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7
Capturing and measuring thematic relatedness [<Journal>]
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
In: Conference papers (2019)
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9
Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings
In: Articles (2019)
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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
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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
Abstract: This paper examines to what degree current deep learning architectures for image caption generation capture spatial language. On the basis of the evaluation of examples of generated captions from the literature we argue that systems capture what objects are in the image data but not where these objects are located: the captions generated by these systems are the output of a language model conditioned on the output of an object detector that cannot capture fine-grained location information. Although language models provide useful knowledge for image captions, we argue that deep learning image captioning architectures should also model geometric relations between objects. ... : 15 pages, 10 figures, Appears in CLASP Papers in Computational Linguistics Vol 1: Proceedings of the Conference on Logic and Machine Learning in Natural Language (LaML 2017), pp. 41-52 ...
Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG; Machine Learning stat.ML; Neural and Evolutionary Computing cs.NE
URL: https://arxiv.org/abs/1807.08133
https://dx.doi.org/10.48550/arxiv.1807.08133
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12
Is it worth it? Budget-related evaluation metrics for model selection ...
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13
Is it worth it? Budget-related evaluation metrics for model selection
In: Conference papers (2018)
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14
Exploring the Functional and Geometric Bias of Spatial Relations Using Neural Language Models
In: Conference papers (2018)
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15
Back to the Future: Logic and Machine Learning
In: Conference papers (2017)
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16
Robot Perception Errors and Human Resolution Strategies in Situated Human-Robot Dialogue
In: Articles (2017)
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17
Assessing the Usefulness of Different Feature Sets for Predicting the Comprehension Difficulty of Text
In: Conference papers (2017)
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18
Towards a Computational Model of Frame of Reference Alignment in Swedish Dialogue
In: Conference papers (2016)
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19
A Model for Attention-Driven Judgements in Type Theory with Records
In: Conference papers (2016)
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20
Fundamentals of Machine Learning for Neural Machine Translation
In: Conference papers (2016)
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