Liir Lab
Home
Members
Publications
Projects
Software
Education
CALCULUS
Common sense and Anticipation enriched Learning of Continuous representations
sUpporting Language UnderStanding
CALCULUS focuses on learning effective anticipatory representations of events and their narrative structures that are trained on language and visual data. The machine learning methods on which CALCULUS will build belong to the family of latent variable models where it will rely on Bayesian probabilistic models and neural networks as starting points. CALCULUS focuses on settings with limited training data that are manually annotated and especially aims at developing novel machine learning paradigms for natural language understanding. CALCULUS also evaluates the inference potential of the anticipatory representations in situations not seen in the training data and for inferring spatial, temporal and causal information in metric real world spaces. The best models for language understanding will be integrated in a demonstrator that translates language to events happening in a 3-D virtual world. See the CALCULUS website for the latest updates.
Period
From
2018-09-01
to
2024-09-30
.
Financed by
European Research Council Advanced Grant H2020-ERC-2017-ADG 788506
Supervised by
Marie-Francine Moens
Staff
Nathan Cornille
Ruben Cartuyvels
Aristotelis Chrysakis
Thierry Deruyttere
Tuur Leeuwenberg
Victor Milewski
Damien Sileo
Graham Spinks
Guillem Collell Talleda
Contact
Marie-Francine Moens
More information can be found on the project website
http://calculus-project.eu/
Publications
Cornille, Nathan & Moens, Marie-Francine Improving Language Understanding in Machines through Anticipation. In
3rd Human Brain Project Curriculum Workshop on Cognitive Systems
. 2019
Spinks, Graham & Moens, Marie-Francine Justifying Diagnosis Decisions by Deep Neural Networks
Journal of Biomedical Informatics
. 2019
Deruyttere, Thierry & Moens, Marie-Francine Giving Commands to a Self-driving Car: A Multimodal Reasoner for Visual Grounding. In
Proceedings of AAAI 2020 Reasoning for Complex Question Answering Workshop
. 2020
Cornille, Nathan & Moens, Marie-Francine Improving Representation Learning with Pervasive Internal Regression (PIR). In
Proceedings of the CSHL Meeting: From Neuroscience to Artificially Intelligent Systems
(
NAISys
). 2020
Spinks, Graham, Cartuyvels, Ruben & Moens, Marie-Francine Learning Grammar in Confined Worlds. In
Proceedings of the International Workshop on Spoken Dialog System Technology
(
IWSDS 2020
). 2020
Aristotelis Chrysakis and Marie-Francine Moens Online Continual Learning from Imbalanced Data. In
Proceedings of the 37th International Conference on Machine Learning
(ICML 2020). 2020
Milewski, Victor, Moens, Marie-Francine & Calixto, Iacer Are Scene Graphs Good Enough to Improve Image Captioning?
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing
. ACL. 2020
Leeuwenberg, Tuur & Moens, Marie-Francine Towards extracting absolute event timelines from English clinical reports.
IEEE/ACM Transactions on Audio, Speech and Language Processing
. 2020
Ruben Cartuyvels, Graham Spinks & Marie-Francine Moens Autoregressive Reasoning over Chains of Facts with Transformers
Proceedings of the 28th International Conference on Computational Linguistics
(COLING 2020). (pp. 6916-6930). ACL. 2020
Graham Spinks and Marie-Francine Moens Structured (De)composable Representations Trained with Neural Networks. In
Proceedings of the 9th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition
(ANNPR 2020), Springer. 2020
Evin Pınar Örnek and Marie-Francine Moens Verbs On Action: Zero Shot Activity Recognition with Videos In
Proceedings of CVPR Workshop on Visual Learning with Limited Labels
. 2020
Graham Spinks & Marie-Francine Moens Structured (De)composable Representations Trained with Neural Networks.
Computers - Special Issue Artificial Neural Networks in Pattern Recognition
(invited publication). 2020
Parisa Kordjamshidi, James Pustejovski & Marie-Francine Moens Representation Learning and Reasoning on Spatial Language for Downstream NLP Tasks. In
Proceedings of EMNLP
(tutorial abstracts) (pp. 28-33). ACL. 2020
Dario Pavllo, Graham Spinks, Thomas Hofmann, Marie-Francine Moens & Aurelien Lucchi Convolutional Generation of Textured 3D Meshes. In
Proceedings of the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS)
(oral presentation). 2020
Guillem Collell & Marie-Francine Moens How Do Simple Transformations of Text and Image Features Impact Cosine-based Semantic Match? In
Proceedings of the 43rd European Conference on Information Retrieval
. Springer. 2020
Deruyttere, Thierry, Milewski, Victor and Moens, Marie-Francine Giving commands to a self-driving car: How to deal with uncertain situations?
Engineering Applications of Artificial Intelligence
, 103, Art.No. 104257, 1-20. 2021
Li, Ruiqi, Zhao, Xiang and Moens, Marie-Francine A Brief Overview of Universal Sentence Representation Methods: A Linguistic View.
ACM Computing Surveys
. 2021
Cartuyvels, Ruben, Spinks, Graham and Moens, Marie-Francine Discrete and Continuous Representations and Processing in Deep Learning: Looking Forward.
AI Open Elsevier
. 2021
Vladimir Araujo, Andrés Villa, Marie-Francine Moens, Alvaro Soto and Marcelo Mendoza Augmenting BERT-style Models with Predictive Coding to Improve Discourse-Level Representations In
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
(EMNLP). 2021
Back to
all projects