no code implementations • NAACL (DeeLIO) 2021 • Dhairya Dalal, Mihael Arcan, Paul Buitelaar
To the best of our knowledge, no prior work has explored the efficacy of augmenting pretrained language models with external causal knowledge for multiple-choice causal question answering.
1 code implementation • NLP4ConvAI (ACL) 2022 • Rajdeep Sarkar, Mihael Arcan, John McCrae
A crucial challenge of such systems is to select facts from a knowledge graph pertinent to the dialogue context for response generation.
no code implementations • NAACL (ACL) 2022 • Ali Hatami, Paul Buitelaar, Mihael Arcan
To calculate the ambiguity of a sentence, we extract the ambiguity scores for all nouns based on the number of senses in WordNet.
no code implementations • ACL (WebNLG, INLG) 2020 • Nivranshu Pasricha, Mihael Arcan, Paul Buitelaar
This paper describes the system submitted by NUIG-DSI to the WebNLG+ challenge 2020 in the RDF-to-text generation task for the English language.
no code implementations • ACL (WebNLG, INLG) 2020 • Nivranshu Pasricha, Mihael Arcan, Paul Buitelaar
Data-to-text generation has recently seen a move away from modular and pipeline architectures towards end-to-end architectures based on neural networks.
no code implementations • VarDial (COLING) 2020 • Bharathi Raja Chakravarthi, Navaneethan Rajasekaran, Mihael Arcan, Kevin McGuinness, Noel E. O’Connor, John P. McCrae
Bilingual lexicons are a vital tool for under-resourced languages and recent state-of-the-art approaches to this leverage pretrained monolingual word embeddings using supervised or semi-supervised approaches.
no code implementations • GWC 2018 • Bharathi Raja Chakravarthi, Mihael Arcan, John P. McCrae
In addition to that, we carried out a manual evaluation of the translations for the Tamil language, where we demonstrate that our approach can aid in improving wordnet resources for under-resourced Dravidian languages.
no code implementations • AMTA 2016 • Rajen Chatterjee, Mihael Arcan, Matteo Negri, Marco Turchi
In recent years, several end-to-end online translation systems have been proposed to successfully incorporate human post-editing feedback in the translation workflow.
no code implementations • ACL (GEM) 2021 • Nivranshu Pasricha, Mihael Arcan, Paul Buitelaar
This paper describes the submission by NUIG-DSI to the GEM benchmark 2021.
no code implementations • 2 Feb 2024 • David W. Vinson, Mihael Arcan, David-Paul Niland, Fionn Delahunty
Employee well-being is a critical concern in the contemporary workplace, as highlighted by the American Psychological Association's 2021 report, indicating that 71% of employees experience stress or tension.
no code implementations • 9 Jan 2024 • Mihael Arcan, David-Paul Niland, Fionn Delahunty
Mental health challenges pose considerable global burdens on individuals and communities.
no code implementations • 8 Sep 2021 • Shardul Suryawanshi, Bharathi Raja Chakravarthi, Mihael Arcan, Suzanne Little, Paul Buitelaar
To enable this analysis, we enhanced an existing dataset by annotating the data with our defined classes, resulting in a dataset of 8, 881 IWT or multimodal memes in the English language (TrollsWithOpinion dataset).
no code implementations • SEMEVAL 2020 • Shardul Suryawanshi, Mihael Arcan, Paul Buitelaar
This work is licensed under a Creative Commons Attribution 4. 0 International Licence.
1 code implementation • COLING 2020 • Rajdeep Sarkar, Koustava Goswami, Mihael Arcan, John P. McCrae
Conversational recommender systems focus on the task of suggesting products to users based on the conversation flow.
no code implementations • 28 Sep 2020 • Daniel Torregrosa, Nivranshu Pasricha, Maraim Masoud, Bharathi Raja Chakravarthi, Juan Alonso, Noe Casas, Mihael Arcan
Rule-based machine translation is a machine translation paradigm where linguistic knowledge is encoded by an expert in the form of rules that translate text from source to target language.
no code implementations • 4 Aug 2020 • Bharathi Raja Chakravarthi, Priya Rani, Mihael Arcan, John P. McCrae
It introduces under-resourced languages in terms of machine translation and how orthographic information can be utilised to improve machine translation.
1 code implementation • LREC 2020 • Shardul Suryawanshi, Bharathi Raja Chakravarthi, Mihael Arcan, Paul Buitelaar
Since there was no publicly available dataset for multimodal offensive meme content detection, we leveraged the memes related to the 2016 U. S. presidential election and created the MultiOFF multimodal meme dataset for offensive content detection dataset.
Ranked #4 on
Meme Classification
on MultiOFF
(F1 metric)
no code implementations • LREC 2020 • John Philip McCrae, Mihael Arcan
In this paper, we present the NUIG system at the TIAD shard task.
no code implementations • LREC 2020 • Shardul Suryawanshi, Bharathi Raja Chakravarthi, Pranav Verma, Mihael Arcan, John Philip McCrae, Paul Buitelaar
Social media are interactive platforms that facilitate the creation or sharing of information, ideas or other forms of expression among people.
no code implementations • WS 2019 • Fionn Delahunty, Robert Johansson, Mihael Arcan
Depression and anxiety are the two most prevalent mental health disorders worldwide, impacting the lives of millions of people each year.
no code implementations • 4 Mar 2019 • Mihael Arcan, John McCrae, Paul Buitelaar
The translation of wordnets is fundamentally complex because of the need to translate all senses of a word including low frequency senses, which is very challenging for current machine translation approaches.
no code implementations • 7 Mar 2018 • Mihael Arcan
In this paper we present a question answering system using a neural network to interpret questions learned from the DBpedia repository.
no code implementations • 7 Sep 2017 • Mihael Arcan, Daniel Torregrosa, Paul Buitelaar
Our work presented in this paper focuses on the translation of terminological expressions represented in semantically structured resources, like ontologies or knowledge graphs.
no code implementations • COLING 2016 • Mihael Arcan, John Philip McCrae, Paul Buitelaar
The translation of wordnets is fundamentally complex because of the need to translate all senses of a word including low frequency senses, which is very challenging for current machine translation approaches.
no code implementations • LREC 2016 • Mihael Arcan, Caoilfhionn Lane, Eoin {\'O} Droighne{\'a}in, Paul Buitelaar
We describe IRIS, a statistical machine translation (SMT) system for translating from English into Irish and vice versa.