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John D. Kelleher
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Journal Articles
- 2024
- [j22]Ammar N. Abbas
, Georgios C. Chasparis
, John D. Kelleher
:
Hierarchical framework for interpretable and specialized deep reinforcement learning-based predictive maintenance. Data Knowl. Eng. 149: 102240 (2024) - 2022
- [j21]Elizabeth Hunter
, John D. Kelleher
:
Validating and Testing an Agent-Based Model for the Spread of COVID-19 in Ireland. Algorithms 15(8): 270 (2022) - [j20]Elizabeth Hunter, John D. Kelleher
:
A review of risk concepts and models for predicting the risk of primary stroke. Frontiers Neuroinformatics 16 (2022) - [j19]Vasudevan Nedumpozhimana, Filip Klubicka, John D. Kelleher
:
Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification. Frontiers Artif. Intell. 5: 813967 (2022) - [j18]Prashanth Nayak
, Rejwanul Haque
, John D. Kelleher
, Andy Way
:
Investigating Contextual Influence in Document-Level Translation. Inf. 13(5): 249 (2022) - [j17]Matthew Nicholson, Rahul Agrahari, Clare Conran, Haythem Assem, John D. Kelleher
:
The interaction of normalisation and clustering in sub-domain definition for multi-source transfer learning based time series anomaly detection. Knowl. Based Syst. 257: 109894 (2022) - 2021
- [j16]Elizabeth Hunter
, John D. Kelleher
:
Adapting an Agent-Based Model of Infectious Disease Spread in an Irish County to COVID-19. Syst. 9(2): 41 (2021) - 2020
- [j15]Aphra Kerr
, Marguerite Barry
, John D. Kelleher
:
Expectations of artificial intelligence and the performativity of ethics: Implications for communication governance. Big Data Soc. 7(1): 205395172091593 (2020) - [j14]Elizabeth Hunter
, Brian Mac Namee, John D. Kelleher:
A Hybrid Agent-Based and Equation Based Model for the Spread of Infectious Diseases. J. Artif. Soc. Soc. Simul. 23(4) (2020) - [j13]Magdalena Kacmajor
, John D. Kelleher
:
Capturing and measuring thematic relatedness. Lang. Resour. Evaluation 54(3): 645-682 (2020) - 2019
- [j12]Alfredo Maldonado, Filip Klubicka, John D. Kelleher
:
Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings. Open Comput. Sci. 9(1): 252-267 (2019) - [j11]Vaibhav Kulkarni
, Abhijit Mahalunkar
, Benoît Garbinato
, John D. Kelleher
:
Examining the Limits of Predictability of Human Mobility. Entropy 21(4): 432 (2019) - [j10]Magdalena Kacmajor
, John D. Kelleher
:
Automatic Acquisition of Annotated Training Corpora for Test-Code Generation. Inf. 10(2): 66 (2019) - 2018
- [j9]Elizabeth Hunter
, Brian Mac Namee, John D. Kelleher
:
Using a Socioeconomic Segregation Burn-in Model to Initialise an Agent-Based Model for Infectious Diseases. J. Artif. Soc. Soc. Simul. 21(4) (2018) - 2017
- [j8]Niels Schütte, Brian Mac Namee
, John D. Kelleher
:
Robot perception errors and human resolution strategies in situated human-robot dialogue. Adv. Robotics 31(5): 243-257 (2017) - [j7]Elizabeth Hunter
, Brian Mac Namee, John D. Kelleher
:
A Taxonomy for Agent-Based Models in Human Infectious Disease Epidemiology. J. Artif. Soc. Soc. Simul. 20(3) (2017) - 2011
- [j6]John D. Kelleher
, Robert J. Ross
, Colm Sloan, Brian Mac Namee
:
The effect of occlusion on the semantics of projective spatial terms: a case study in grounding language in perception. Cogn. Process. 12(1): 95-108 (2011) - [j5]Niels Schütte, John D. Kelleher, Brian Mac Namee:
Automatic Annotation of Referring Expressions in Situated Dialogues. Int. J. Comput. Linguistics Appl. 2(1-2): 175-190 (2011) - 2009
- [j4]John D. Kelleher
, Fintan J. Costello
:
Applying Computational Models of Spatial Prepositions to Visually Situated Dialog. Comput. Linguistics 35(2): 271-306 (2009) - 2006
- [j3]John D. Kelleher
:
Attention driven reference resolution in multimodal contexts. Artif. Intell. Rev. 25(1-2): 21-35 (2006) - 2005
- [j2]John D. Kelleher
, Fintan J. Costello
, Josef van Genabith:
Dynamically structuring, updating and interrelating representations of visual and linguistic discourse context. Artif. Intell. 167(1-2): 62-102 (2005) - 2004
- [j1]John D. Kelleher
, Josef van Genabith:
Visual Salience and Reference Resolution in Simulated 3-D Environments. Artif. Intell. Rev. 21(3-4): 253-267 (2004)
Conference and Workshop Papers
- 2024
- [c89]Patrick Cormac English, Erfan A. Shams, John D. Kelleher, Julie Carson-Berndsen:
Following the Embedding: Identifying Transition Phenomena in Wav2vec 2.0 Representations of Speech Audio. ICASSP 2024: 6685-6689 - [c88]Aayush Jain, Philip Long, Valeria Villani, John D. Kelleher, Maria Chiara Leva:
CoBT: Collaborative Programming of Behaviour Trees from One Demonstration for Robot Manipulation. ICRA 2024: 12993-12999 - [c87]Jeffrey Sardina, John D. Kelleher, Declan O'Sullivan:
TWIG: Towards pre-hoc Hyperparameter Optimisation and Cross-Graph Generalisation via Simulated KGE Models. ICSC 2024: 122-129 - 2023
- [c86]Yasmin Moslem, Rejwanul Haque, John D. Kelleher, Andy Way:
Adaptive Machine Translation with Large Language Models. EAMT 2023: 227-237 - [c85]Maja Popovic, Vasudevan Nedumpozhimana, Meegan Gower, Sneha Rautmare, Nishtha Jain, John D. Kelleher:
Using MT for multilingual covid-19 case load prediction from social media texts. EAMT 2023: 461-470 - [c84]Shakra Mehak
, Maria Chiara Leva
, John D. Kelleher
, Michael Guilfoyle
:
Action Classification in Human Robot Interaction Cells in Manufacturing: Moving Towards Mutual Performance Monitoring Capacity. ICMLT 2023: 214-220 - [c83]Patrick Cormac English, John D. Kelleher, Julie Carson-Berndsen:
Discovering Phonetic Feature Event Patterns in Transformer Embeddings. INTERSPEECH 2023: 4733-4737 - [c82]Filip Klubicka, Vasudevan Nedumpozhimana, John D. Kelleher
:
Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space. MWE@EACL 2023: 45-57 - [c81]Vasudevan Nedumpozhimana, Sneha Rautmare, Meegan Gower, Nishtha Jain, Maja Popovic, Patricia Buffini, John D. Kelleher:
Medical Concept Mention Identification in Social Media Posts Using a Small Number of Sample References. RANLP 2023: 777-784 - [c80]Annika Lindh
, Robert J. Ross
, John D. Kelleher
:
Show, Prefer and Tell: Incorporating User Preferences into Image Captioning. SAC 2023: 1139-1142 - [c79]Yasmin Moslem, Gianfranco Romani, Mahdi Molaei, John D. Kelleher, Rejwanul Haque, Andy Way:
Domain Terminology Integration into Machine Translation: Leveraging Large Language Models. WMT 2023: 902-911 - [c78]Filip Klubicka, John D. Kelleher:
Probing Taxonomic and Thematic Embeddings for Taxonomic Information. GWC 2023: 1-13 - 2022
- [c77]Jeffrey Sardina
, Callie Sardina
, John D. Kelleher
, Declan O'Sullivan
:
Analysis of Attention Mechanisms in Box-Embedding Systems. AICS 2022: 68-80 - [c76]Yasmin Moslem
, Rejwanul Haque, John D. Kelleher, Andy Way:
Domain-Specific Text Generation for Machine Translation. AMTA 2022: 14-30 - [c75]Filip Klubicka, John D. Kelleher:
Probing with Noise: Unpicking the Warp and Weft of Embeddings. BlackboxNLP@EMNLP 2022: 404-417 - [c74]Ammar N. Abbas
, Georgios C. Chasparis
, John D. Kelleher
:
Interpretable Input-Output Hidden Markov Model-Based Deep Reinforcement Learning for the Predictive Maintenance of Turbofan Engines. DaWaK 2022: 133-148 - 2021
- [c73]Peru Bhardwaj
, John D. Kelleher
, Luca Costabello, Declan O'Sullivan:
Poisoning Knowledge Graph Embeddings via Relation Inference Patterns. ACL/IJCNLP (1) 2021: 1875-1888 - [c72]Peru Bhardwaj, John D. Kelleher
, Luca Costabello, Declan O'Sullivan:
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods. EMNLP (1) 2021: 8225-8239 - [c71]Elizabeth Hunter
, Bryony L. McGarry
, John D. Kelleher
:
Simulating Delay in Seeking Treatment for Stroke Due to COVID-19 Concerns with a Hybrid Agent-Based and Equation-Based Model. ESSA 2021: 379-391 - [c70]Somayeh Jafaritazehjani, Gwénolé Lecorvé, Damien Lolive, John D. Kelleher
:
Style as Sentiment Versus Style as Formality: The Same or Different? ICANN (5) 2021: 487-499 - [c69]Vasudevan Nedumpozhimana, John D. Kelleher:
Finding BERT's Idiomatic Key. MWE@ACL-IJCNLP 2021: 57-62 - 2020
- [c68]Anh-Duong Trinh, Robert J. Ross, John D. Kelleher:
Energy-based Neural Modelling for Large-Scale Multiple Domain Dialogue State Tracking. SPNLP@EMNLP 2020: 33-42 - [c67]Esra Zihni, Vince Istvan Madai, Ahmed A. Khalil, Ivana Galinovic, Jochen B. Fiebach, John D. Kelleher, Dietmar Frey, Michelle Livne:
Multimodal Fusion Strategies for Outcome Prediction in Stroke. HEALTHINF 2020: 421-428 - [c66]Annika Lindh
, Robert J. Ross, John D. Kelleher:
Language-Driven Region Pointer Advancement for Controllable Image Captioning. COLING 2020: 1922-1935 - [c65]Somayeh Jafaritazehjani, Gwénolé Lecorvé, Damien Lolive, John D. Kelleher:
Style versus Content: A distinction without a (learnable) difference? COLING 2020: 2169-2180 - [c64]Eoin Rogers, Robert J. Ross
, John D. Kelleher:
Modelling Interleaved Activities Using Language Models. ECMS 2020: 183-189 - [c63]Anh-Duong Trinh, Robert J. Ross
, John D. Kelleher
:
F-Measure Optimisation and Label Regularisation for Energy-Based Neural Dialogue State Tracking Models. ICANN (2) 2020: 798-810 - [c62]Abhijit Mahalunkar
, John D. Kelleher
:
Mutual Information Decay Curves and Hyper-parameter Grid Search Design for Recurrent Neural Architectures. ICONIP (5) 2020: 616-624 - [c61]Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher:
English WordNet Random Walk Pseudo-Corpora. LREC 2020: 4893-4902 - [c60]Simon Dobnik
, John D. Kelleher
, Christine Howes
:
Local Alignment of Frame of Reference Assignment in English and Swedish Dialogue. Spatial Cognition 2020: 251-267 - 2019
- [c59]Vaibhav Kulkarni
, Abhijit Mahalunkar
, Benoît Garbinato
, John D. Kelleher
:
On the Inability of Markov Models to Capture Criticality in Human Mobility. ICANN (3) 2019: 484-497 - [c58]Murhaf Hossari, Soumyabrata Dev
, John D. Kelleher
:
TEST: A Terminology Extraction System for Technology Related Terms. ICCAE 2019: 78-81 - [c57]Eoin Rogers, John D. Kelleher
, Robert J. Ross:
Language Model Co-occurrence Linking for Interleaved Activity Discovery. MLN 2019: 70-84 - [c56]Fei Wang, Robert J. Ross, John D. Kelleher:
Update Frequency and Background Corpus Selection in Dynamic TF-IDF Models for First Story Detection. PACLING 2019: 206-217 - [c55]Giancarlo D. Salton, John D. Kelleher:
Persistence pays off: Paying Attention to What the LSTM Gating Mechanism Persists. RANLP 2019: 1052-1059 - [c54]Fei Wang, Robert J. Ross, John D. Kelleher:
Bigger versus Similar: Selecting a Background Corpus for First Story Detection Based on Distributional Similarity. RANLP 2019: 1312-1320 - [c53]Anh-Duong Trinh, Robert J. Ross, John D. Kelleher
:
Capturing Dialogue State Variable Dependencies with an Energy-based Neural Dialogue State Tracker. SIGdial 2019: 75-84 - [c52]Filip Klubicka, Alfredo Maldonado, Abhijit Mahalunkar, John D. Kelleher:
Synthetic, yet natural: Properties of WordNet random walk corpora and the impact of rare words on embedding performance. GWC 2019: 140-150 - 2018
- [c51]Elizabeth Hunter, Brian Mac Namee, John D. Kelleher:
A Comparison of Agent-Based Models and Equation Based Models for Infectious Disease Epidemiology. AICS 2018: 33-44 - [c50]Aram Ter-Sarkisov, John D. Kelleher, Bernadette Earley, Michael Keane, Robert J. Ross:
Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network. BMVC 2018: 272 - [c49]Annika Lindh
, Robert J. Ross
, Abhijit Mahalunkar
, Giancarlo D. Salton
, John D. Kelleher
:
Generating Diverse and Meaningful Captions - Unsupervised Specificity Optimization for Image Captioning. ICANN (1) 2018: 176-187 - [c48]Abhijit Mahalunkar
, John D. Kelleher
:
Using Regular Languages to Explore the Representational Capacity of Recurrent Neural Architectures. ICANN (3) 2018: 189-198 - [c47]Fei Wang, Robert J. Ross, John D. Kelleher
:
Exploring Online Novelty Detection Using First Story Detection Models. IDEAL (1) 2018: 107-116 - [c46]Eoin Rogers, Robert J. Ross
, John D. Kelleher
:
Evaluating Sequence Discovery Systems in an Abstraction-Aware Manner. AIAI 2018: 261-272 - [c45]Filip Klubicka, Giancarlo D. Salton, John D. Kelleher:
Is it worth it? Budget-related evaluation metrics for model selection. LREC 2018 - [c44]Ivan Bacher, Brian Mac Namee
, John D. Kelleher
:
Scoped: Evaluating A Composite Visualisation of the Scope Chain Hierarchy Within Source Code. VISSOFT 2018: 117-121 - [c43]Ivan Bacher, Brian Mac Namee
, John D. Kelleher
:
The Code Mini-Map Visualisation: Encoding Conceptual Structures Within Source Code. VISSOFT 2018: 127-131 - 2017
- [c42]Brian Mac Namee, John D. Kelleher, Noel Fitzpatrick:
Assessing the Usefulness of Different Feature Sets for Predicting the Comprehension Difficulty of Text. AICS 2017: 12-25 - [c41]Aram Ter-Sarkisov, Robert J. Ross
, John D. Kelleher
:
Bootstrapping Labelled Dataset Construction for Cow Tracking and Behavior Analysis. CRV 2017: 277-284 - [c40]Ivan Bacher, Brian Mac Namee, John D. Kelleher
:
The Code-Map Metaphor - A Review of Its Use Within Software Visualisations. VISIGRAPP (3: IVAPP) 2017: 17-28 - [c39]Giancarlo D. Salton, Robert J. Ross, John D. Kelleher:
Attentive Language Models. IJCNLP(1) 2017: 441-450 - [c38]Fei Wang, Hector-Hugo Franco-Penya, John D. Kelleher
, John Pugh, Robert J. Ross
:
An Analysis of the Application of Simplified Silhouette to the Evaluation of k-means Clustering Validity. MLDM 2017: 291-305 - [c37]Eoin Rogers, Robert J. Ross
, John D. Kelleher
:
Tackling the Interleaving Problem in Activity Discovery. PAAMS (Special Sessions) 2017: 313-314 - [c36]Andrew Hines
, John D. Kelleher
:
A framework for post-stroke quality of life prediction using structured prediction. QoMEX 2017: 1-6 - [c35]Giancarlo D. Salton, Robert J. Ross, John D. Kelleher:
Idiom Type Identification with Smoothed Lexical Features and a Maximum Margin Classifier. RANLP 2017: 642-651 - [c34]Ivan Bacher, Brian Mac Namee, John D. Kelleher
:
Scoped: Visualising the Scope Chain Within Source Code. EuroVis (Short Papers) 2017: 115-119 - 2016
- [c33]Giancarlo D. Salton, Robert J. Ross, John D. Kelleher
:
Idiom Token Classification using Sentential Distributed Semantics. ACL (1) 2016 - [c32]Elizabeth Hunter, Brian Mac Namee, John D. Kelleher:
An Open Data Driven Epidemiological Agent-Based Model for Irish Towns. AICS 2016: 92-103 - [c31]Eoin Rogers, John D. Kelleher, Robert J. Ross:
Towards a Deep Learning-based Activity Discovery System. AICS 2016: 184-191 - [c30]Eoin Rogers, John D. Kelleher
, Robert J. Ross
:
Using Topic Modelling Algorithms for Hierarchical Activity Discovery. ISAmI 2016: 41-48 - [c29]Pierre Beauguitte, Bryan Duggan, John D. Kelleher:
A Corpus of Annotated Irish Traditional Dance Music Recordings: Design and Benchmark Evaluations. ISMIR 2016: 53-59 - [c28]Ivan Bacher, Brian Mac Namee, John D. Kelleher
:
On Using Tree Visualisation Techniques to Support Source Code Comprehension. VISSOFT 2016: 91-95 - [c27]Ivan Bacher, Brian Mac Namee, John D. Kelleher
:
Using Icicle Trees to Encode the Hierarchical Structure of Source Code. EuroVis (Short Papers) 2016: 97-101 - 2014
- [c26]Niels Schütte, John D. Kelleher
, Brian Mac Namee
:
The Effect of Sensor Errors in Situated Human-Computer Dialogue. VL@COLING 2014: 1-8 - [c25]Simon Dobnik, John D. Kelleher:
Exploration of functional semantics of prepositions from corpora of descriptions of visual scenes. VL@COLING 2014: 33-37 - [c24]Giancarlo D. Salton, Robert J. Ross, John D. Kelleher:
An Empirical Study of the Impact of Idioms on Phrase Based Statistical Machine Translation of English to Brazilian-Portuguese. HyTra@EACL 2014: 36-41 - [c23]Niels Schütte, John D. Kelleher
, Brian Mac Namee
:
Clarification Dialogues for Perception-based Errors in Situated Human-Computer Dialogues. MMRWHRI@ICMI 2014: 25-26 - [c22]Giancarlo D. Salton, Robert J. Ross, John D. Kelleher:
Evaluation of a Substitution Method for Idiom Transformation in Statistical Machine Translation. MWE@EACL 2014: 38-42 - [c21]Magdalena Kacmajor, John D. Kelleher
:
DIT: Summarisation and Semantic Expansion in Evaluating Semantic Similarity. SemEval@COLING 2014: 230-234 - [c20]Arun Kumar Jayapal
, Martin Emms, John D. Kelleher:
TCDSCSS: Dimensionality Reduction to Evaluate Texts of Varying Lengths - an IR Approach. SemEval@COLING 2014: 619-623 - 2013
- [c19]Robert J. Ross, John D. Kelleher:
Accuracy and Timeliness in ML Based Activity Recognition. AAAI Workshop: Plan, Activity, and Intent Recognition 2013 - [c18]Yan Li, Brian Mac Namee
, John D. Kelleher
:
Expecting the Unexpected: Measure the Uncertainties for Mobile Robot Path Planning in Dynamic Environment. TAROS 2013: 363-374 - 2012
- [c17]Nick Hawes, Matthew Klenk, Kate Lockwood, Graham S. Horn, John D. Kelleher:
Towards a Cognitive System that Can Recognize Spatial Regions Based on Context. AAAI 2012: 200-206 - [c16]Dmitry Strunkin, Brian Mac Namee
, John D. Kelleher
:
An Investigation Into Feature Selection for Oncological Survival Prediction. ITNG 2012: 764-768 - [c15]Mark Dunne, Brian Mac Namee
, John D. Kelleher
:
The Turning, Stretching and Boxing Technique: A Step in the Right Direction. IVA 2012: 363-369 - 2011
- [c14]Colm Sloan, John D. Kelleher
, Brian Mac Namee
:
Feasibility study of utility-directed behaviour for computer game agents. Advances in Computer Entertainment Technology 2011: 5 - [c13]Joana Hois, Robert J. Ross, John D. Kelleher, John A. Bateman:
Workshop on Computational Models of Spatial Language Interpretation - CoSLI-2 in conjunction with CogSci 2011. CogSci 2011 - [c12]Colm Sloan, John D. Kelleher
, Brian Mac Namee
:
Feeling the ambiance: using smart ambiance to increase contextual awareness in game agents. FDG 2011: 298-300 - 2010
- [c11]John D. Kelleher, Robert J. Ross, Brian Mac Namee, Colm Sloan:
Situating Spatial Templates for Human-Robot Interaction. AAAI Fall Symposium: Dialog with Robots 2010 - [c10]Niels Schuette, John D. Kelleher, Brian Mac Namee:
Visual Salience and Reference Resolution in Situated Dialogues: A Corpus-based Evaluation. AAAI Fall Symposium: Dialog with Robots 2010 - 2009
- [c9]Nicholas Hanlon, Brian Mac Namee
, John D. Kelleher
:
Just Say It: An Evaluation of Speech Interfaces for Augmented Reality Design Applications. AICS 2009: 134-143 - 2008
- [c8]John D. Kelleher, Brian Mac Namee:
Referring Expression Generation Challenge 2008 DIT System Descriptions (DIT-FBI, DIT-TVAS, DIT-CBSR, DIT-RBR, DIT-FBI-CBSR, DIT-TVAS-RBR). INLG 2008 - 2007
- [c7]Michael Brenner, Nick Hawes, John D. Kelleher, Jeremy L. Wyatt:
Mediating between Qualitative and Quantitative Representations for Task-Orientated Human-Robot Interaction. IJCAI 2007: 2072-2077 - 2006
- [c6]John D. Kelleher
, Geert-Jan M. Kruijff:
Incremental Generation of Spatial Referring Expressions in Situated Dialog. ACL 2006 - [c5]John D. Kelleher
, Geert-Jan M. Kruijff, Fintan J. Costello:
Proximity in Context: An Empirically Grounded Computational Model of Proximity for Processing Topological Spatial Expressions. ACL 2006 - [c4]Geert-Jan M. Kruijff, John D. Kelleher
, Gregor Berginc, Ales Leonardis:
Structural descriptions in human-assisted robot visual learning. HRI 2006: 343-344 - [c3]Geert-Jan M. Kruijff, John D. Kelleher
, Nick Hawes
:
Information Fusion for Visual Reference Resolution in Dynamic Situated Dialogue. PIT 2006: 117-128 - 2005
- [c2]John D. Kelleher, Geert-Jan M. Kruijff:
A Context-dependent Algorithm for Generating Locative Expressions in Physically Situated Environments. ENLG 2005 - 2004
- [c1]John D. Kelleher, Josef van Genabith:
Exploiting Visual Salience for the Generation of Referring Expressions. FLAIRS 2004: 911-916
Parts in Books or Collections
- 2011
- [p1]John D. Kelleher
:
Visual salience and the other one. Salience - Multidisciplinary Perspectives on its Function in Discourse 2011: 205-228
Editorship
- 2020
- [e2]Brian Davis, Yvette Graham, John D. Kelleher, Yaji Sripada:
Proceedings of the 13th International Conference on Natural Language Generation, INLG 2020, Dublin, Ireland, December 15-18, 2020. Association for Computational Linguistics 2020, ISBN 978-1-952148-54-5 [contents] - 2010
- [e1]John D. Kelleher, Brian Mac Namee, Ielka van der Sluis, Anja Belz, Albert Gatt, Alexander Koller:
INLG 2010 - Proceedings of the Sixth International Natural Language Generation Conference, July 7-9, 2010, Trim, Co. Meath, Ireland. The Association for Computer Linguistics 2010 [contents]
Informal and Other Publications
- 2024
- [i35]Jeffrey Sardina, John D. Kelleher, Declan O'Sullivan:
TWIG: Towards pre-hoc Hyperparameter Optimisation and Cross-Graph Generalisation via Simulated KGE Models. CoRR abs/2402.06097 (2024) - [i34]Ammar N. Abbas, Chidera W. Amazu, Joseph Mietkiewicz, Houda Briwa, Andres Alonzo Perez, Gabriele Baldissone, Micaela Demichela, Georgios C. Chasparis, John D. Kelleher, Maria Chiara Leva:
Analyzing Operator States and the Impact of AI-Enhanced Decision Support in Control Rooms: A Human-in-the-Loop Specialized Reinforcement Learning Framework for Intervention Strategies. CoRR abs/2402.13219 (2024) - [i33]Vasudevan Nedumpozhimana, John D. Kelleher:
Topic Aware Probing: From Sentence Length Prediction to Idiom Identification how reliant are Neural Language Models on Topic? CoRR abs/2403.02009 (2024) - [i32]Aayush Jain, Philip Long, Valeria Villani, John D. Kelleher, Maria Chiara Leva:
CoBT: Collaborative Programming of Behaviour Trees from One Demonstration for Robot Manipulation. CoRR abs/2404.05870 (2024) - [i31]Elizabeth Hunter, John D. Kelleher:
Estimating Population Burden of Stroke with an Agent-Based Model. CoRR abs/2405.19934 (2024) - [i30]Ammar N. Abbas, Shakra Mehak, Georgios C. Chasparis, John D. Kelleher, Michael Guilfoyle, Maria Chiara Leva, Aswin K. Ramasubramanian:
Safety-Driven Deep Reinforcement Learning Framework for Cobots: A Sim2Real Approach. CoRR abs/2407.02231 (2024) - 2023
- [i29]Filip Klubicka, John D. Kelleher:
Probing Taxonomic and Thematic Embeddings for Taxonomic Information. CoRR abs/2301.10656 (2023) - [i28]Filip Klubicka, Vasudevan Nedumpozhimana, John D. Kelleher:
Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space. CoRR abs/2304.14333 (2023) - [i27]Anya Belz
, Craig Thomson, Ehud Reiter, Gavin Abercrombie, Jose Maria Alonso-Moral
, Mohammad Arvan, Jackie Chi Kit Cheung, Mark Cieliebak, Elizabeth Clark, Kees van Deemter, Tanvi Dinkar, Ondrej Dusek, Steffen Eger, Qixiang Fang, Albert Gatt, Dimitra Gkatzia, Javier González-Corbelle, Dirk Hovy, Manuela Hürlimann, Takumi Ito, John D. Kelleher, Filip Klubicka, Huiyuan Lai, Chris van der Lee, Emiel van Miltenburg, Yiru Li, Saad Mahamood, Margot Mieskes, Malvina Nissim, Natalie Parde, Ondrej Plátek, Verena Rieser, Pablo Mosteiro Romero, Joel R. Tetreault, Antonio Toral, Xiaojun Wan, Leo Wanner, Lewis Watson
, Diyi Yang:
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP. CoRR abs/2305.01633 (2023) - [i26]Yasmin Moslem, Gianfranco Romani, Mahdi Molaei, Rejwanul Haque
, John D. Kelleher, Andy Way:
Domain Terminology Integration into Machine Translation: Leveraging Large Language Models. CoRR abs/2310.14451 (2023) - [i25]Ammar N. Abbas, Georgios C. Chasparis, John D. Kelleher:
Specialized Deep Residual Policy Safe Reinforcement Learning-Based Controller for Complex and Continuous State-Action Spaces. CoRR abs/2310.14788 (2023) - [i24]Ammar N. Abbas, Georgios C. Chasparis, John D. Kelleher:
Hierarchical Framework for Interpretable and Probabilistic Model-Based Safe Reinforcement Learning. CoRR abs/2310.18811 (2023) - 2022
- [i23]Na Li, John D. Kelleher, Robert J. Ross:
Detecting Interlocutor Confusion in Situated Human-Avatar Dialogue: A Pilot Study. CoRR abs/2206.02436 (2022) - [i22]Ammar N. Abbas
, Georgios C. Chasparis, John D. Kelleher:
Interpretable Hidden Markov Model-Based Deep Reinforcement Learning Hierarchical Framework for Predictive Maintenance of Turbofan Engines. CoRR abs/2206.13433 (2022) - [i21]Yasmin Moslem, Rejwanul Haque
, John D. Kelleher, Andy Way:
Domain-Specific Text Generation for Machine Translation. CoRR abs/2208.05909 (2022) - [i20]Filip Klubicka, John D. Kelleher:
Probing with Noise: Unpicking the Warp and Weft of Embeddings. CoRR abs/2210.12206 (2022) - 2021
- [i19]Peru Bhardwaj, John D. Kelleher, Luca Costabello, Declan O'Sullivan:
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods. CoRR abs/2111.03120 (2021) - [i18]Peru Bhardwaj, John D. Kelleher, Luca Costabello, Declan O'Sullivan:
Poisoning Knowledge Graph Embeddings via Relation Inference Patterns. CoRR abs/2111.06345 (2021) - 2020
- [i17]Magdalena Kacmajor, John D. Kelleher, Filip Klubicka, Alfredo Maldonado:
Semantic Relatedness and Taxonomic Word Embeddings. CoRR abs/2002.06235 (2020) - [i16]Annika Lindh, Robert J. Ross, John D. Kelleher:
Language-Driven Region Pointer Advancement for Controllable Image Captioning. CoRR abs/2011.14901 (2020) - [i15]Abhijit Mahalunkar, John D. Kelleher:
Mutual Information Decay Curves and Hyper-Parameter Grid Search Design for Recurrent Neural Architectures. CoRR abs/2012.04632 (2020) - 2019
- [i14]John D. Kelleher, Simon Dobnik:
Referring to the recently seen: reference and perceptual memory in situated dialog. CoRR abs/1903.09866 (2019) - [i13]Abhijit Mahalunkar, John D. Kelleher:
Multi-Element Long Distance Dependencies: Using SPk Languages to Explore the Characteristics of Long-Distance Dependencies. CoRR abs/1907.06048 (2019) - 2018
- [i12]Aram Ter-Sarkisov, Robert J. Ross, John D. Kelleher, Bernadette Earley, Michael Keane:
Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network. CoRR abs/1807.01972 (2018) - [i11]Filip Klubicka, Giancarlo D. Salton, John D. Kelleher:
Is it worth it? Budget-related evaluation metrics for model selection. CoRR abs/1807.06998 (2018) - [i10]John D. Kelleher, Simon Dobnik:
What is not where: the challenge of integrating spatial representations into deep learning architectures. CoRR abs/1807.08133 (2018) - [i9]Simon Dobnik, John D. Kelleher:
Modular Mechanistic Networks: On Bridging Mechanistic and Phenomenological Models with Deep Neural Networks in Natural Language Processing. CoRR abs/1807.09844 (2018) - [i8]Vaibhav Kulkarni, Abhijit Mahalunkar, Benoît Garbinato, John D. Kelleher:
On the Inability of Markov Models to Capture Criticality in Human Mobility. CoRR abs/1807.11386 (2018) - [i7]Abhijit Mahalunkar, John D. Kelleher:
Using Regular Languages to Explore the Representational Capacity of Recurrent Neural Architectures. CoRR abs/1808.05128 (2018) - [i6]Abhijit Mahalunkar, John D. Kelleher:
Understanding Recurrent Neural Architectures by Analyzing and Synthesizing Long Distance Dependencies in Benchmark Sequential Datasets. CoRR abs/1810.02966 (2018) - [i5]Giancarlo D. Salton, John D. Kelleher:
Persistence pays off: Paying Attention to What the LSTM Gating Mechanism Persists. CoRR abs/1810.04437 (2018) - [i4]Giancarlo D. Salton, Robert J. Ross, John D. Kelleher:
Exploring the Use of Attention within an Neural Machine Translation Decoder States to Translate Idioms. CoRR abs/1810.06695 (2018) - [i3]Annika Lindh, Robert J. Ross, Abhijit Mahalunkar, Giancarlo D. Salton, John D. Kelleher:
Generating Diverse and Meaningful Captions. CoRR abs/1812.08126 (2018) - [i2]Murhaf Hossari, Soumyabrata Dev, John D. Kelleher:
TEST: A Terminology Extraction System for Technology Related Terms. CoRR abs/1812.09541 (2018) - 2017
- [i1]Aram Ter-Sarkisov, Robert J. Ross, John D. Kelleher:
Bootstrapping Labelled Dataset Construction for Cow Tracking and Behavior Analysis. CoRR abs/1703.10571 (2017)
Coauthor Index
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
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