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20172021
most citedGenerating Diverse and Meaningful Captions

16 citations · 20 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CL2020

Language-Driven Region Pointer Advancement for Controllable Image Captioning

Annika Lindh, Robert J. Ross, John D. Kelleher

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 t…

cs.CL2020

Semantic Relatedness and Taxonomic Word Embeddings

Magdalena Kacmajor, John D. Kelleher, Filip Klubicka +1

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…

cs.CL2018

Exploring the Use of Attention within an Neural Machine Translation Decoder States to Translate Idioms

Giancarlo D. Salton, Robert J. Ross, John D. Kelleher

Idioms pose problems to almost all Machine Translation systems. This type of language is very frequent in day-to-day language use and cannot be simply ignored. The recent interest…

cs.CL2018

Is it worth it? Budget-related evaluation metrics for model selection

Filip Klubička, Giancarlo D. Salton, John D. Kelleher

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…

cs.CL2018

Modular Mechanistic Networks: On Bridging Mechanistic and Phenomenological Models with Deep Neural Networks in Natural Language Processing

Simon Dobnik, John D. Kelleher

Natural language processing (NLP) can be done using either top-down (theory driven) and bottom-up (data driven) approaches, which we call mechanistic and phenomenological respectiv…