Maria Lomeli

According to our database, Maria Lomeli authored at least 23 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

TOOLVERIFIER: Generalization to New Tools via Self-Verification.

Dheeraj Mekala, Jason Weston, Jack Lanchantin, Roberta Raileanu, Maria Lomeli, Jingbo Shang, Jane Dwivedi-Yu

CoRR, 2024

The Faiss library.

Matthijs Douze, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazaré, Maria Lomeli, Lucas Hosseini, Hervé Jégou

CoRR, 2024

2023

Improving Wikipedia verifiability with AI.

Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick S. H. Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Michele Bevilacqua, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel

Nat. Mac. Intell., October, 2023

Atlas: Few-shot Learning with Retrieval Augmented Language Models.

Gautier Izacard, Patrick S. H. Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave

J. Mach. Learn. Res., 2023

In-Context Pretraining: Language Modeling Beyond Document Boundaries.

Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Scott Yih, Mike Lewis

CoRR, 2023

RA-DIT: Retrieval-Augmented Dual Instruction Tuning.

Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Rich James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Scott Yih

CoRR, 2023

Augmented Language Models: a Survey.

Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom

CoRR, 2023

Toolformer: Language Models Can Teach Themselves to Use Tools.

Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom

CoRR, 2023

Toolformer: Language Models Can Teach Themselves to Use Tools.

Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

EditEval: An Instruction-Based Benchmark for Text Improvements.

Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang, Maria Lomeli, Patrick S. H. Lewis, Gautier Izacard, Edouard Grave, Sebastian Riedel, Fabio Petroni

CoRR, 2022

Few-shot Learning with Retrieval Augmented Language Models.

Gautier Izacard, Patrick S. H. Lewis, Maria Lomeli, Lucas Hosseini, Fabio Petroni, Timo Schick, Jane Dwivedi-Yu, Armand Joulin, Sebastian Riedel, Edouard Grave

CoRR, 2022

Improving Wikipedia Verifiability with AI.

Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick S. H. Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, Sebastian Riedel

CoRR, 2022

2021

Testing Web Enabled Simulation at Scale Using Metamorphic Testing.

John Ahlgren, Maria Eugenia Berezin, Kinga Bojarczuk, Elena Dulskyte, Inna Dvortsova, Johann George, Natalija Gucevska, Mark Harman, Maria Lomeli, Erik Meijer, Silvia Sapora, Justin Spahr-Summers

Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice, 2021

Measurement Challenges for Cyber Cyber Digital Twins: Experiences from the Deployment of Facebook's WW Simulation System.

Kinga Bojarczuk, Natalija Gucevska, Simon M. M. Lucas, Inna Dvortsova, Mark Harman, Erik Meijer, Silvia Sapora, Johann George, Maria Lomeli, Rubmary Rojas

Proceedings of the ESEM '21: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, 2021

Facebook's Cyber-Cyber and Cyber-Physical Digital Twins.

John Ahlgren, Kinga Bojarczuk, Sophia Drossopoulou, Inna Dvortsova, Johann George, Natalija Gucevska, Mark Harman, Maria Lomeli, Simon M. M. Lucas, Erik Meijer, Steve Omohundro, Rubmary Rojas, Silvia Sapora, Norm Zhou

Proceedings of the EASE 2021: Evaluation and Assessment in Software Engineering, 2021

2020

General Latent Feature Models for Heterogeneous Datasets.

Isabel Valera, Melanie F. Pradier, Maria Lomeli, Zoubin Ghahramani

J. Mach. Learn. Res., 2020

Masking schemes for universal marginalisers.

Divya Gautam, Maria Lomeli, Kostis Gourgoulias, Daniel H. Thompson, Saurabh Johri

CoRR, 2020

2019

Antithetic and Monte Carlo kernel estimators for partial rankings.

Maria Lomeli, Mark Rowland, Arthur Gretton, Zoubin Ghahramani

Stat. Comput., 2019

Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs.

Robert Walecki, Kostis Gourgoulias, Adam Baker, Chris Hart, Chris Lucas, Max Zwiessele, Albert Buchard, Maria Lomeli, Yura Perov, Saurabh Johri

CoRR, 2019

2018

Universal Marginalizer for Amortised Inference and Embedding of Generative Models.

Robert Walecki, Albert Buchard, Kostis Gourgoulias, Chris Hart, Maria Lomeli, Alexandre K. W. Navarro, Max Zwiessele, Yura Perov, Saurabh Johri

CoRR, 2018

2015

On a class of σ-stable Poisson-Kingman models and an effective marginalized sampler.

Stefano Favaro, Maria Lomeli, Yee Whye Teh

Stat. Comput., 2015

A hybrid sampler for Poisson-Kingman mixture models.

Maria Lomeli, Stefano Favaro, Yee Whye Teh

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Kernel Adaptive Metropolis-Hastings.

Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton

Proceedings of the 31th International Conference on Machine Learning, 2014