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ORCIDPasquale Minervini
Person information
- affiliation: University of Edinburgh, UK
- affiliation (former): University College London, Centre for Artificial Intelligence, UK
- affiliation (former): University of Bari Aldo Moro, Department of Computer Science, Italy
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2020 – today
- 2024
[j7]Simone Scardapane, Alessandro Baiocchi, Alessio Devoto, Valerio Marsocci, Pasquale Minervini, Jary Pomponi:
Conditional computation in neural networks: Principles and research trends. Intelligenza Artificiale 18(1): 175-190 (2024)- [c66]Jesus Solano, Mardhiyah Sanni, Oana-Maria Camburu, Pasquale Minervini:
SparseFit: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations. ACL (1) 2024: 2053-2077 - [c65]Yu Zhao, Yuanbin Qu, Konrad Staniszewski, Szymon Tworkowski, Wei Liu, Piotr Milos, Yuxiang Wu, Pasquale Minervini:
Analysing The Impact of Sequence Composition on Language Model Pre-Training. ACL (1) 2024: 7897-7912 - [c64]Hetong Wang, Pasquale Minervini, Edoardo M. Ponti:
Probing the Emergence of Cross-lingual Alignment during LLM Training. ACL (Findings) 2024: 12159-12173 - [c63]Xuanli He, Yuxiang Wu, Oana-Maria Camburu, Pasquale Minervini, Pontus Stenetorp:
Using Natural Language Explanations to Improve Robustness of In-context Learning. ACL (1) 2024: 13477-13499 - [c62]Aryo Gema, Pasquale Minervini, Luke Daines, Tom Hope, Beatrice Alex:
Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain. ClinicalNLP@NAACL 2024: 91-104 - [c61]Burcu Sayin, Pasquale Minervini, Jacopo Staiano, Andrea Passerini:
Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain. ClinicalNLP@NAACL 2024: 218-237 - [c60]Aryo Gema, Chaeeun Lee, Pasquale Minervini, Luke Daines, T. Ian Simpson, Beatrice Alex:
Edinburgh Clinical NLP at MEDIQA-CORR 2024: Guiding Large Language Models with Hints. ClinicalNLP@NAACL 2024: 488-501 - [c59]Emile van Krieken, Pasquale Minervini, Edoardo M. Ponti, Antonio Vergari:
On the Independence Assumption in Neurosymbolic Learning. ICML 2024 - [c58]Aryo Gema, Giwon Hong, Pasquale Minervini, Luke Daines, Beatrice Alex:
Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4. SemEval@NAACL 2024: 1894-1904 - [i65]Yu Zhao
, Yuanbin Qu, Konrad Staniszewski, Szymon Tworkowski, Wei Liu, Piotr Milos, Yuxiang Wu, Pasquale Minervini:
Analysing The Impact of Sequence Composition on Language Model Pre-Training. CoRR abs/2402.13991 (2024) - [i64]Mattia Setzu, Marta Marchiori Manerba, Pasquale Minervini, Debora Nozza:
FairBelief - Assessing Harmful Beliefs in Language Models. CoRR abs/2402.17389 (2024) - [i63]Rustam Abdumalikov, Pasquale Minervini, Yova Kementchedjhieva:
Answerability in Retrieval-Augmented Open-Domain Question Answering. CoRR abs/2403.01461 (2024) - [i62]Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun, Kevin K. Nejad, Felipe Yáñez, Bati Yilmaz, Kangjoo Lee, Alexandra O. Cohen, Valentina Borghesani, Anton Pashkov, Daniele Marinazzo, Jonathan Nicholas, Alessandro Salatiello, Ilia Sucholutsky, Pasquale Minervini, Sepehr Razavi, Roberta Rocca, Elkhan Yusifov, Tereza Okalova, Nianlong Gu, Martin Ferianc, Mikail Khona, Kaustubh R. Patil, Pui-Shee Lee, Rui Mata, Nicholas E. Myers, Jennifer K. Bizley, Sebastian Musslick, Isil Poyraz Bilgin, Guiomar Niso, Justin M. Ales, Michael Gaebler, N. Apurva Ratan Murty, Leyla Loued-Khenissi, Anna Behler, Chloe M. Hall, Jessica Dafflon, Sherry Dongqi Bao, Bradley C. Love:
Large language models surpass human experts in predicting neuroscience results. CoRR abs/2403.03230 (2024) - [i61]Simone Scardapane, Alessandro Baiocchi, Alessio Devoto, Valerio Marsocci, Pasquale Minervini, Jary Pomponi:
Conditional computation in neural networks: principles and research trends. CoRR abs/2403.07965 (2024) - [i60]Burcu Sayin, Pasquale Minervini, Jacopo Staiano, Andrea Passerini:
Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain. CoRR abs/2403.20288 (2024) - [i59]Aryo Pradipta Gema, Giwon Hong, Pasquale Minervini, Luke Daines, Beatrice Alex:
Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4. CoRR abs/2404.00484 (2024) - [i58]Giwon Hong, Aryo Pradipta Gema, Rohit Saxena, Xiaotang Du, Ping Nie, Yu Zhao, Laura Perez-Beltrachini, Max Ryabinin, Xuanli He, Clémentine Fourrier, Pasquale Minervini:
The Hallucinations Leaderboard - An Open Effort to Measure Hallucinations in Large Language Models. CoRR abs/2404.05904 (2024) - [i57]Emile van Krieken, Pasquale Minervini, Edoardo M. Ponti, Antonio Vergari:
On the Independence Assumption in Neurosymbolic Learning. CoRR abs/2404.08458 (2024) - [i56]Jordi Armengol-Estapé, Rodrigo C. O. Rocha, Jackson Woodruff, Pasquale Minervini, Michael F. P. O'Boyle:
Forklift: An Extensible Neural Lifter. CoRR abs/2404.16041 (2024) - [i55]Xuanli He, Jun Wang, Qiongkai Xu, Pasquale Minervini, Pontus Stenetorp, Benjamin I. P. Rubinstein, Trevor Cohn:
Transferring Troubles: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning. CoRR abs/2404.19597 (2024) - [i54]Simon Chi Lok U, Jie He, Pasquale Minervini, Jeff Z. Pan:
Evaluating the Adversarial Robustness of Retrieval-Based In-Context Learning for Large Language Models. CoRR abs/2405.15984 (2024) - [i53]Aryo Pradipta Gema, Chaeeun Lee, Pasquale Minervini, Luke Daines, T. Ian Simpson, Beatrice Alex:
Edinburgh Clinical NLP at MEDIQA-CORR 2024: Guiding Large Language Models with Hints. CoRR abs/2405.18028 (2024) - [i52]Aryo Pradipta Gema, Joshua Ong Jun Leang, Giwon Hong, Alessio Devoto, Alberto Carlo Maria Mancino, Rohit Saxena, Xuanli He, Yu Zhao, Xiaotang Du, Mohammad Reza Ghasemi Madani, Claire Barale, Robert McHardy, Joshua Harris, Jean Kaddour, Emile van Krieken, Pasquale Minervini:
Are We Done with MMLU? CoRR abs/2406.04127 (2024) - [i51]Alessio Devoto, Yu Zhao, Simone Scardapane, Pasquale Minervini:
A Simple and Effective L2 Norm-Based Strategy for KV Cache Compression. CoRR abs/2406.11430 (2024) - [i50]Hetong Wang, Pasquale Minervini, Edoardo M. Ponti:
Probing the Emergence of Cross-lingual Alignment during LLM Training. CoRR abs/2406.13229 (2024) - [i49]Gayane Ghazaryan, Erik Arakelyan, Pasquale Minervini, Isabelle Augenstein:
SynDARin: Synthesising Datasets for Automated Reasoning in Low-Resource Languages. CoRR abs/2406.14425 (2024) - [i48]Georgy Tyukin, Gbètondji J.-S. Dovonon, Jean Kaddour, Pasquale Minervini:
Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models. CoRR abs/2407.15516 (2024) - [i47]Alessio Devoto, Federico Alvetreti, Jary Pomponi, Paolo Di Lorenzo, Pasquale Minervini, Simone Scardapane:
Adaptive Layer Selection for Efficient Vision Transformer Fine-Tuning. CoRR abs/2408.08670 (2024) - 2023
- [j6]Mohan Timilsina, Dirk Fey, Samuele Buosi, Adrianna Janik, Luca Costabello, Enric Carcereny, Delvys Rodriguez Abreu, Manuel Cobo, Rafael Castro, Reyes Bernabé, Pasquale Minervini, Maria Torrente, Mariano Provencio, Vít Novácek:
Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer. J. Biomed. Informatics 144: 104424 (2023) - [c57]Pasquale Minervini, Luca Franceschi, Mathias Niepert:
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models. AAAI 2023: 9200-9208 - [c56]Medina Andresel, Trung-Kien Tran, Csaba Domokos, Pasquale Minervini, Daria Stepanova:
Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs. CIKM 2023: 15-24 - [c55]Mohammad Reza Ghasemi Madani, Pasquale Minervini:
REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization. CoNLL 2023: 587-602 - [c54]Han Zhou, Ignacio Iacobacci, Pasquale Minervini:
XQA-DST: Multi-Domain and Multi-Lingual Dialogue State Tracking. EACL (Findings) 2023: 969-979 - [c53]Mohan Timilsina, Samuele Buosi, Adrianna Janik, Pasquale Minervini, Luca Costabello, Maria Torrente, Mariano Provencio, Virginia Calvo, Carlos Camps, Ana L. Ortega, Bartomeu Massutí, M. Rosario Garcia Campelo, Edel del Barco, Joaquim Bosch-Barrera, Vít Novácek:
Machine Learning Survival Models for Relapse Prediction in a Early Stage Lung Cancer Patient. IJCNN 2023: 1-8 - [c52]Erik Arakelyan, Pasquale Minervini, Daniel Daza, Michael Cochez, Isabelle Augenstein:
Adapting Neural Link Predictors for Data-Efficient Complex Query Answering. NeurIPS 2023 - [c51]Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner:
No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models. NeurIPS 2023 - [p4]Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren:
Approximate Answering of Graph Queries. Compendium of Neurosymbolic Artificial Intelligence 2023: 373-386 - [i46]Erik Arakelyan, Pasquale Minervini, Isabelle Augenstein:
Adapting Neural Link Predictors for Complex Query Answering. CoRR abs/2301.12313 (2023) - [i45]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Oana-Maria Camburu, Marek Rei:
Logical Reasoning for Natural Language Inference Using Generated Facts as Atoms. CoRR abs/2305.13214 (2023) - [i44]Jesus Solano, Oana-Maria Camburu, Pasquale Minervini:
SPARSEFIT: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations. CoRR abs/2305.13235 (2023) - [i43]Aryo Pradipta Gema, Dominik Grabarczyk, Wolf De Wulf, Piyush Borole, Javier Antonio Alfaro, Pasquale Minervini, Antonio Vergari, Ajitha Rajan:
Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy Tasks. CoRR abs/2305.19979 (2023) - [i42]Aryo Pradipta Gema, Luke Daines, Pasquale Minervini, Beatrice Alex:
Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain. CoRR abs/2307.03042 (2023) - [i41]Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J. Kusner:
No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models. CoRR abs/2307.06440 (2023) - [i40]Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan, Max Berrendorf, Daniel Daza, Mikhail Galkin, Pasquale Minervini, Mathias Niepert, Hongyu Ren:
Approximate Answering of Graph Queries. CoRR abs/2308.06585 (2023) - [i39]Manuel Dileo, Pasquale Minervini, Matteo Zignani, Sabrina Gaito:
Temporal Smoothness Regularisers for Neural Link Predictors. CoRR abs/2309.09045 (2023) - [i38]Mohammad Reza Ghasemi Madani, Pasquale Minervini:
REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization. CoRR abs/2310.14418 (2023) - [i37]Xuanli He, Yuxiang Wu, Oana-Maria Camburu, Pasquale Minervini, Pontus Stenetorp:
Using Natural Language Explanations to Improve Robustness of In-context Learning for Natural Language Inference. CoRR abs/2311.07556 (2023) - [i36]Bartosz Wójcik, Alessio Devoto, Karol Pustelnik, Pasquale Minervini, Simone Scardapane:
Adaptive Computation Modules: Granular Conditional Computation For Efficient Inference. CoRR abs/2312.10193 (2023) - 2022
- [c50]Mohan Timilsina, Samuele Bousi, Dirk Fey, Adrianna Janik, Maria Torrente, Mariano Provencio, Alberto Bermúdez, Enric Carcereny, Luca Costabello, Delvys Rodriguez Abreu, Manuel Cobo, Rafael Castro, Reyes Bernabé, Maria Guirado, Pasquale Minervini, Vít Novácek:
Integration of Clinical Information and Imputed Aneuploidy Scores to Enhance Relapse Prediction in Early Stage Lung Cancer Patients. AMIA 2022 - [c49]Saadullah Amin, Pasquale Minervini, David Chang, Pontus Stenetorp, Guenter Neumann:
MedDistant19: Towards an Accurate Benchmark for Broad-Coverage Biomedical Relation Extraction. COLING 2022: 2259-2277 - [c48]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Marek Rei:
Logical Reasoning with Span-Level Predictions for Interpretable and Robust NLI Models. EMNLP 2022: 3809-3823 - [c47]Yuxiang Wu, Yu Zhao, Baotian Hu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel:
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks. EMNLP 2022: 5184-5196 - [c46]Pasquale Minervini, Erik Arakelyan, Daniel Daza, Michael Cochez:
Complex Query Answering with Neural Link Predictors (Extended Abstract). IJCAI 2022: 5309-5313 - [c45]Matthew Morris, Pasquale Minervini, Phil Blunsom:
Learning Proof Path Selection Policies in Neural Theorem Proving. NeSy 2022: 64-87 - [c44]Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel:
ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective. NeurIPS 2022 - [i35]Wanshui Li, Pasquale Minervini:
Differentiable Reasoning over Long Stories - Assessing Systematic Generalisation in Neural Models. CoRR abs/2203.10620 (2022) - [i34]Saadullah Amin, Pasquale Minervini, David Chang, Günter Neumann, Pontus Stenetorp:
MedDistant19: A Challenging Benchmark for Distantly Supervised Biomedical Relation Extraction. CoRR abs/2204.04779 (2022) - [i33]Han Zhou, Ignacio Iacobacci, Pasquale Minervini:
XQA-DST: Multi-Domain and Multi-Lingual Dialogue State Tracking. CoRR abs/2204.05895 (2022) - [i32]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Marek Rei:
Logical Reasoning with Span Predictions: Span-level Logical Atoms for Interpretable and Robust NLI Models. CoRR abs/2205.11432 (2022) - [i31]Yihong Chen, Pushkar Mishra, Luca Franceschi, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel:
ReFactorGNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective. CoRR abs/2207.09980 (2022) - [i30]Pasquale Minervini, Luca Franceschi, Mathias Niepert:
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models. CoRR abs/2209.04862 (2022) - [i29]Andrew J. Wren, Pasquale Minervini, Luca Franceschi, Valentina Zantedeschi:
Learning Discrete Directed Acyclic Graphs via Backpropagation. CoRR abs/2210.15353 (2022) - [i28]Yuxiang Wu, Yu Zhao, Baotian Hu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel:
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks. CoRR abs/2210.16773 (2022) - [i27]Adrianna Janik, Maria Torrente, Luca Costabello, Virginia Calvo, Brian Walsh, Carlos Camps, Sameh K. Mohamed, Ana L. Ortega, Vít Novácek, Bartomeu Massutí, Pasquale Minervini, M. Rosario Garcia Campelo, Edel del Barco, Joaquim Bosch-Barrera, Ernestina Menasalvas, Mohan Timilsina, Mariano Provencio:
Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients. CoRR abs/2211.09856 (2022) - 2021
- [j5]Patrick S. H. Lewis, Yuxiang Wu, Linqing Liu, Pasquale Minervini, Heinrich Küttler, Aleksandra Piktus, Pontus Stenetorp, Sebastian Riedel:
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them. Trans. Assoc. Comput. Linguistics 9: 1098-1115 (2021) - [c43]Yuxiang Wu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel:
Training Adaptive Computation for Open-Domain Question Answering with Computational Constraints. ACL/IJCNLP (2) 2021: 447-453 - [c42]Yihong Chen, Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp:
Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations. AKBC 2021 - [c41]Agnieszka Dobrowolska, Antonio Vergari, Pasquale Minervini:
Neural Concept Formation in Knowledge Graphs. AKBC 2021 - [c40]Sameh K. Mohamed, Brian Walsh, Mohan Timilsina, Vít Novácek, Maria Torrente, Fabio Franco, Mariano Provencio, Adrianna Janik, Luca Costabello, Pontus Stenetorp, Pasquale Minervini:
On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer. AMIA 2021 - [c39]Zhengyao Jiang, Pasquale Minervini, Minqi Jiang, Tim Rocktäschel:
Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning. AAMAS 2021: 674-682 - [c38]Vasudev Lal, Somak Aditya, Yezhou Yang, Pasquale Minervini, Sandya Mannarswamy:
First Workshop on Knowledge Injection in Neural Networks (KINN). CIKM 2021: 4882-4883 - [c37]Mattia Setzu, Anna Monreale, Pasquale Minervini:
TRIPLEx: Triple Extraction for Explanation. CogMI 2021: 44-53 - [c36]Daniel de Vassimon Manela, David Errington, Thomas Fisher, Boris van Breugel, Pasquale Minervini:
Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models. EACL 2021: 2232-2242 - [c35]Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez:
Complex Query Answering with Neural Link Predictors. ICLR 2021 - [c34]Patrick Betz, Mathias Niepert, Pasquale Minervini, Heiner Stuckenschmidt:
Backpropagating through Markov Logic Networks. NeSy 2021: 67-81 - [c33]Mathias Niepert, Pasquale Minervini, Luca Franceschi:
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions. NeurIPS 2021: 14567-14579 - [p3]Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp, Edward Grefenstette, Tim Rocktäschel:
Learning Reasoning Strategies in End-to-End Differentiable Proving. Neuro-Symbolic Artificial Intelligence 2021: 280-293 - [i26]Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih:
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. CoRR abs/2101.00133 (2021) - [i25]Daniel de Vassimon Manela, David Errington, Thomas Fisher, Boris van Breugel, Pasquale Minervini:
Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models. CoRR abs/2101.09688 (2021) - [i24]Zhengyao Jiang, Pasquale Minervini, Minqi Jiang, Tim Rocktäschel:
Grid-to-Graph: Flexible Spatial Relational Inductive Biases for Reinforcement Learning. CoRR abs/2102.04220 (2021) - [i23]Patrick S. H. Lewis, Yuxiang Wu, Linqing Liu, Pasquale Minervini, Heinrich Küttler, Aleksandra Piktus, Pontus Stenetorp, Sebastian Riedel:
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them. CoRR abs/2102.07033 (2021) - [i22]Mathias Niepert, Pasquale Minervini, Luca Franceschi:
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions. CoRR abs/2106.01798 (2021) - [i21]Yuxiang Wu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel:
Training Adaptive Computation for Open-Domain Question Answering with Computational Constraints. CoRR abs/2107.02102 (2021) - [i20]Yihong Chen, Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp:
Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations. CoRR abs/2110.02834 (2021) - [i19]Jatin Chauhan, Priyanshu Gupta, Pasquale Minervini:
A Probabilistic Framework for Knowledge Graph Data Augmentation. CoRR abs/2110.13205 (2021) - 2020
- [c32]Pasquale Minervini, Matko Bosnjak, Tim Rocktäschel, Sebastian Riedel, Edward Grefenstette:
Differentiable Reasoning on Large Knowledge Bases and Natural Language. AAAI 2020: 5182-5190 - [c31]Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz, Phil Blunsom:
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. ACL 2020: 4157-4165 - [c30]Yuxiang Wu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel:
Don't Read Too Much Into It: Adaptive Computation for Open-Domain Question Answering. SustaiNLP@EMNLP 2020: 63-72 - [c29]Johannes Welbl, Pasquale Minervini, Max Bartolo, Pontus Stenetorp, Sebastian Riedel:
Undersensitivity in Neural Reading Comprehension. EMNLP (Findings) 2020: 1152-1165 - [c28]Yuxiang Wu, Sebastian Riedel, Pasquale Minervini, Pontus Stenetorp:
Don't Read Too Much Into It: Adaptive Computation for Open-Domain Question Answering. EMNLP (1) 2020: 3029-3039 - [c27]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Sebastian Riedel, Tim Rocktäschel:
Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training. EMNLP (1) 2020: 8281-8291 - [c26]Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp, Edward Grefenstette, Tim Rocktäschel:
Learning Reasoning Strategies in End-to-End Differentiable Proving. ICML 2020: 6938-6949 - [c25]Sewon Min, Jordan L. Boyd-Graber, Chris Alberti, Danqi Chen, Eunsol Choi, Michael Collins, Kelvin Guu, Hannaneh Hajishirzi, Kenton Lee, Jennimaria Palomaki, Colin Raffel, Adam Roberts, Tom Kwiatkowski, Patrick S. H. Lewis, Yuxiang Wu, Heinrich Küttler, Linqing Liu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel, Sohee Yang, Minjoon Seo, Gautier Izacard, Fabio Petroni, Lucas Hosseini, Nicola De Cao, Edouard Grave, Ikuya Yamada, Sonse Shimaoka, Masatoshi Suzuki, Shumpei Miyawaki, Shun Sato, Ryo Takahashi, Jun Suzuki, Martin Fajcik, Martin Docekal, Karel Ondrej, Pavel Smrz, Hao Cheng, Yelong Shen, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Sejr Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih:
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. NeurIPS (Competition and Demos) 2020: 86-111 - [p2]Federico Bianchi, Gaetano Rossiello, Luca Costabello, Matteo Palmonari, Pasquale Minervini:
Knowledge Graph Embeddings and Explainable AI. Knowledge Graphs for eXplainable Artificial Intelligence 2020: 49-72 - [p1]Pasquale Minervini, Matko Bosnjak, Tim Rocktäschel, Sebastian Riedel, Edward Grefenstette:
Differentiable Reasoning on Large Knowledge Bases and Natural Language. Knowledge Graphs for eXplainable Artificial Intelligence 2020: 125-142 - [i18]Johannes Welbl, Pasquale Minervini, Max Bartolo, Pontus Stenetorp, Sebastian Riedel:
Undersensitivity in Neural Reading Comprehension. CoRR abs/2003.04808 (2020) - [i17]Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Sebastian Riedel, Tim Rocktäschel:
There is Strength in Numbers: Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training. CoRR abs/2004.07790 (2020) - [i16]Federico Bianchi, Gaetano Rossiello, Luca Costabello, Matteo Palmonari, Pasquale Minervini:
Knowledge Graph Embeddings and Explainable AI. CoRR abs/2004.14843 (2020) - [i15]Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp, Edward Grefenstette, Tim Rocktäschel:
Learning Reasoning Strategies in End-to-End Differentiable Proving. CoRR abs/2007.06477 (2020) - [i14]Minqi Jiang, Jelena Luketina, Nantas Nardelli, Pasquale Minervini, Philip H. S. Torr, Shimon Whiteson, Tim Rocktäschel:
WordCraft: An Environment for Benchmarking Commonsense Agents. CoRR abs/2007.09185 (2020) - [i13]Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez:
Complex Query Answering with Neural Link Predictors. CoRR abs/2011.03459 (2020) - [i12]Yuxiang Wu, Sebastian Riedel, Pasquale Minervini, Pontus Stenetorp:
Don't Read Too Much into It: Adaptive Computation for Open-Domain Question Answering. CoRR abs/2011.05435 (2020)
2010 – 2019
- 2019
- [c24]Leon Weber, Pasquale Minervini, Jannes Münchmeyer, Ulf Leser, Tim Rocktäschel:
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language. ACL (1) 2019: 6151-6161 - [c23]Alexander I. Cowen-Rivers, Pasquale Minervini, Sebastian Riedel, Tim Rocktäschel, Jun Wang, Matko Bosnjak:
Neural Variational Inference For Estimating Knowledge Graph Embedding Uncertainty. NeSy@IJCAI 2019 - [c22]Emir Muñoz, Pasquale Minervini, Matthias Nickles:
Embedding cardinality constraints in neural link predictors. SAC 2019: 2243-2250 - [i11]Alexander I. Cowen-Rivers, Pasquale Minervini, Tim Rocktäschel, Matko Bosnjak, Sebastian Riedel, Jun Wang:
Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings. CoRR abs/1906.04985 (2019) - [i10]Leon Weber, Pasquale Minervini, Jannes Münchmeyer, Ulf Leser, Tim Rocktäschel:
NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language. CoRR abs/1906.06187 (2019) - [i9]Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz, Phil Blunsom:
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. CoRR abs/1910.03065 (2019) - [i8]Pasquale Minervini, Matko Bosnjak, Tim Rocktäschel, Sebastian Riedel, Edward Grefenstette:
Differentiable Reasoning on Large Knowledge Bases and Natural Language. CoRR abs/1912.10824 (2019) - 2018
- [j4]Pasquale Minervini, Volker Tresp, Claudia d'Amato, Nicola Fanizzi:
Adaptive Knowledge Propagation in Web Ontologies. ACM Trans. Web 12(1): 2:1-2:28 (2018) - [c21]Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel:
Convolutional 2D Knowledge Graph Embeddings. AAAI 2018: 1811-1818 - [c20]Dirk Weissenborn, Pasquale Minervini, Isabelle Augenstein, Johannes Welbl, Tim Rocktäschel, Matko Bosnjak, Jeff Mitchell, Thomas Demeester, Tim Dettmers, Pontus Stenetorp, Sebastian Riedel:
Jack the Reader - A Machine Reading Framework. ACL (4) 2018: 25-30 - [c19]