Segui
Pasquale Minervini
Titolo
Citata da
Citata da
Anno
Convolutional 2d knowledge graph embeddings
T Dettmers, P Minervini, P Stenetorp, S Riedel
AAAI 2017, 2017
19782017
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them
P Lewis, Y Wu, L Liu, P Minervini, H Küttler, A Piktus, P Stenetorp, ...
TACL 2021, 2021
1182021
Adversarial sets for regularising neural link predictors
P Minervini, T Demeester, T Rocktäschel, S Riedel
UAI 2017, 2017
1062017
Differentiable Reasoning on Large Knowledge Bases and Natural Language
P Minervini, M Bosnjak, T Rocktäschel, S Riedel, E Grefenstette
AAAI 2020 (Oral), 125-142, 2020
982020
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
L Weber, P Minervini, J Münchmeyer, U Leser, T Rocktäschel
ACL 2019, 2019
952019
Adversarially regularising neural NLI models to integrate logical background knowledge
P Minervini, S Riedel
CoNLL 2018, 2018
932018
Knowledge Graph Embeddings and Explainable AI
F Bianchi, G Rossiello, L Costabello, M Palmonari, P Minervini
IOS Press, 2020
74*2020
Complex Query Answering with Neural Link Predictors
E Arakelyan, D Daza, P Minervini, M Cochez
ICLR 2021 (Oral, Outstanding Paper Award), 2021
652021
Learning Reasoning Strategies in End-to-End Differentiable Proving
P Minervini, S Riedel, P Stenetorp, E Grefenstette, T Rocktäschel
ICML 2020, 2020
632020
Make up your mind! Adversarial generation of inconsistent natural language explanations
OM Camburu, B Shillingford, P Minervini, T Lukasiewicz, P Blunsom
ACL 2019, 2019
572019
Regularizing knowledge graph embeddings via equivalence and inversion axioms
P Minervini, L Costabello, E Muñoz, V Nováček, PY Vandenbussche
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017
562017
NeurIPS 2020 EfficientQA competition: Systems, analyses and lessons learned
S Min, J Boyd-Graber, C Alberti, D Chen, E Choi, M Collins, K Guu, ...
Proceedings of the NeurIPS 2020 Competition and Demonstration Track, PMLR …, 2021
532021
Towards neural theorem proving at scale
P Minervini, M Bosnjak, T Rocktäschel, S Riedel
arXiv preprint arXiv:1807.08204, 2018
492018
Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models
DV Manela, D Errington, T Fisher, B van Breugel, P Minervini
EACL 2021 (Oral), 2021
37*2021
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions
M Niepert, P Minervini, L Franceschi
NeurIPS 2021, 2021
302021
Avoiding the hypothesis-only bias in natural language inference via ensemble adversarial training
J Stacey, P Minervini, H Dubossarsky, S Riedel, T Rocktäschel
EMNLP 2020, 2020
29*2020
Can real-time machine translation overcome language barriers in distributed requirements engineering?
F Calefato, F Lanubile, P Minervini
2010 5th IEEE International Conference on Global Software Engineering, 257-264, 2010
292010
Scalable learning of entity and predicate embeddings for knowledge graph completion
P Minervini, N Fanizzi, C d'Amato, F Esposito
2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015
212015
Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations
Y Chen, P Minervini, S Riedel, P Stenetorp
AKBC 2021, 2021
192021
Extrapolation in NLP
J Mitchell, P Minervini, P Stenetorp, S Riedel
arXiv preprint arXiv:1805.06648, 2018
182018
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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