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Pasquale Minervini
Pasquale Minervini
University of Edinburgh, Miniml.AI, ELLIS Scholar
Bestätigte E-Mail-Adresse bei ed.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Convolutional 2d knowledge graph embeddings
T Dettmers, P Minervini, P Stenetorp, S Riedel
AAAI 2017, 2017
32342017
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
2112021
Complex Query Answering with Neural Link Predictors
E Arakelyan, D Daza, P Minervini, M Cochez
ICLR 2021 (Oral, Outstanding Paper Award), 2021
1502021
Adversarially regularising neural NLI models to integrate logical background knowledge
P Minervini, S Riedel
CoNLL 2018, 2018
1252018
Adversarial sets for regularising neural link predictors
P Minervini, T Demeester, T Rocktäschel, S Riedel
UAI 2017, 2017
1222017
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language
L Weber, P Minervini, J Münchmeyer, U Leser, T Rocktäschel
ACL 2019, 2019
1212019
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
1202020
Knowledge Graph Embeddings and Explainable AI
F Bianchi, G Rossiello, L Costabello, M Palmonari, P Minervini
IOS Press, 2020
1192020
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
107*2021
Make up your mind! Adversarial generation of inconsistent natural language explanations
OM Camburu, B Shillingford, P Minervini, T Lukasiewicz, P Blunsom
ACL 2019, 2019
1052019
Learning Reasoning Strategies in End-to-End Differentiable Proving
P Minervini, S Riedel, P Stenetorp, E Grefenstette, T Rocktäschel
ICML 2020, 2020
992020
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions
M Niepert, P Minervini, L Franceschi
NeurIPS 2021, 2021
982021
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
782021
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
702017
Towards neural theorem proving at scale
P Minervini, M Bosnjak, T Rocktäschel, S Riedel
NAMPI 2018, 2018
572018
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
53*2020
Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations
Y Chen, P Minervini, S Riedel, P Stenetorp
AKBC 2021, 2021
462021
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks
Y Wu, Y Zhao, B Hu, P Minervini, P Stenetorp, S Riedel
EMNLP 2022, 2022
422022
Parameter-efficient fine-tuning of llama for the clinical domain
AP Gema, P Minervini, L Daines, T Hope, B Alex
arXiv preprint arXiv:2307.03042, 2023
322023
Are We Done with MMLU?
AP Gema, JOJ Leang, G Hong, A Devoto, ACM Mancino, R Saxena, X He, ...
NAACL 2025, 2025
31*2025
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