Pasquale Minervini

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Sebastian RiedelHonorary Professor @ University College London, Researcher @ DeepMindVerified email at cs.ucl.ac.uk
Tim RocktäschelDirector and Open-Endedness Team Lead at Google DeepMind, Professor of AI at UCL, Fellow ELLISVerified email at cs.ucl.ac.uk
Aryo Pradipta GemaUniversity of EdinburghVerified email at ed.ac.uk
Tim DettmersAllen Institute for AI; Carnegie Mellon UniversityVerified email at allenai.org
Luca CostabelloAccenture LabsVerified email at accenture.com
Erik ArakelyanUniversity of Copenhagen (UCPH)Verified email at di.ku.dk
Yu ZhaoUniversity of EdinburghVerified email at ed.ac.uk
Yuxiang WuUniversity College London | Weco AIVerified email at ucl.ac.uk
Vit NovacekFaculty of Informatics, Masaryk University / Masaryk Memorial Cancer InstituteVerified email at fi.muni.cz
Xuanli HeUCLVerified email at monash.edu
Oana-Maria CamburuPrincipal Research Fellow, University College LondonVerified email at ucl.ac.uk
Matko BošnjakGoogle DeepMindVerified email at deepmind.com
Alessio DevotoPhD Student, La Sapienza, University of RomeVerified email at uniroma1.it
Michael CochezAssistant Professor, Vrije Universiteit AmsterdamVerified email at vu.nl
Giwon HongUniversity of EdinburghVerified email at ed.ac.uk
Edward GrefenstetteDirector of Research, Google DeepMind | Honorary Professor, UCLVerified email at google.com
Haim DubossarskyLecturer, Queen Mary University of LondonVerified email at qmul.ac.uk
Joe StaceyImperial College LondonVerified email at imperial.ac.uk
Luca FranceschiAmazon Web ServicesVerified email at amazon.de
Rohit SaxenaUniversity of EdinburghVerified email at ed.ac.uk

Pasquale Minervini

University of Edinburgh, Miniml.AI, ELLIS Scholar

Verified email at ed.ac.uk - Homepage

Machine Learning Natural Language Processing Machine Reasoning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Convolutional 2d knowledge graph embeddings T Dettmers, P Minervini, P Stenetorp, S Riedel AAAI 2017, 2017	3188	2017
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	211	2021
Complex Query Answering with Neural Link Predictors E Arakelyan, D Daza, P Minervini, M Cochez ICLR 2021 (Oral, Outstanding Paper Award), 2021	147	2021
Adversarially regularising neural NLI models to integrate logical background knowledge P Minervini, S Riedel CoNLL 2018, 2018	124	2018
Adversarial sets for regularising neural link predictors P Minervini, T Demeester, T Rocktäschel, S Riedel UAI 2017, 2017	122	2017
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	120	2020
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language L Weber, P Minervini, J Münchmeyer, U Leser, T Rocktäschel ACL 2019, 2019	120	2019
Knowledge Graph Embeddings and Explainable AI F Bianchi, G Rossiello, L Costabello, M Palmonari, P Minervini IOS Press, 2020	118	2020
Make up your mind! Adversarial generation of inconsistent natural language explanations OM Camburu, B Shillingford, P Minervini, T Lukasiewicz, P Blunsom ACL 2019, 2019	105	2019
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	103*	2021
Learning Reasoning Strategies in End-to-End Differentiable Proving P Minervini, S Riedel, P Stenetorp, E Grefenstette, T Rocktäschel ICML 2020, 2020	98	2020
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions M Niepert, P Minervini, L Franceschi NeurIPS 2021, 2021	96	2021
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	75	2021
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	70	2017
Towards neural theorem proving at scale P Minervini, M Bosnjak, T Rocktäschel, S Riedel NAMPI 2018, 2018	57	2018
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	54*	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	46	2021
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	42	2022
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	31	2010
No train no gain: Revisiting efficient training algorithms for transformer-based language models J Kaddour, O Key, P Nawrot, P Minervini, MJ Kusner NeurIPS 2023, 2023	30	2023

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