| Toolformer: Language models can teach themselves to use tools T Schick, J Dwivedi-Yu, R Dessì, R Raileanu, M Lomeli, L Zettlemoyer, ... arXiv preprint arXiv:2302.04761, 2023 | 361 | 2023 |
| Few-shot learning with retrieval augmented language models G Izacard, P Lewis, M Lomeli, L Hosseini, F Petroni, T Schick, ... arXiv preprint arXiv:2208.03299, 2022 | 190 | 2022 |
| Augmented language models: a survey G Mialon, R Dessì, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ... arXiv preprint arXiv:2302.07842, 2023 | 169 | 2023 |
| Kernel Adaptive Metropolis–Hastings. D Sejdinovic, H Strathmann, M Lomeli-Garcia, C Andrieu, A Gretton ICML, 1665-1673, 2014 | 56 | 2014 |
| Testing web enabled simulation at scale using metamorphic testing J Ahlgren, M Berezin, K Bojarczuk, E Dulskyte, I Dvortsova, J George, ... 2021 IEEE/ACM 43rd International Conference on Software Engineering …, 2021 | 39 | 2021 |
| General latent feature models for heterogeneous datasets I Valera, MF Pradier, M Lomeli, Z Ghahramani The Journal of Machine Learning Research 21 (1), 4027-4075, 2020 | 27 | 2020 |
| Facebook’s cyber–cyber and cyber–physical digital twins J Ahlgren, K Bojarczuk, S Drossopoulou, I Dvortsova, J George, ... Evaluation and Assessment in Software Engineering, 1-9, 2021 | 22 | 2021 |
| A marginal sampler for σ-stable Poisson–Kingman mixture models M Lomelí, S Favaro, YW Teh Journal of Computational and Graphical Statistics, 2015 | 22 | 2015 |
| Antithetic and Monte Carlo kernel estimators for partial rankings M Lomeli, M Rowland, A Gretton, Z Ghahramani Statistics and Computing 29, 1127-1147, 2019 | 17 | 2019 |
| Measurement challenges for cyber cyber digital twins: Experiences from the deployment of Facebook's ww simulation system K Bojarczuk, N Gucevska, S Lucas, I Dvortsova, M Harman, E Meijer, ... Proceedings of the 15th ACM/IEEE International Symposium on Empirical …, 2021 | 13 | 2021 |
| On the stick-breaking representation of σ-stable Poisson–Kingman models S Favaro, M Lomeli, B Nipoti, YW Teh Electronic Journal of Statistics 8 (1), 1063-1085, 2014 | 11 | 2014 |
| Improving wikipedia verifiability with ai F Petroni, S Broscheit, A Piktus, P Lewis, G Izacard, L Hosseini, ... Nature Machine Intelligence 5 (10), 1142-1148, 2023 | 9 | 2023 |
| EditEval: An Instruction-Based Benchmark for Text Improvements J Dwivedi-Yu, T Schick, Z Jiang, M Lomeli, P Lewis, G Izacard, E Grave, ... arXiv preprint arXiv:2209.13331, 2022 | 8 | 2022 |
| Testing Web Enabled Simulation at Scale Using Metamorphic Testing. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice … J Ahlgren, ME Berezin, K Bojarczuk, E Dulskyte, I Dvortsova, J George, ... IEEE, 140ś149, 2021 | 6 | 2021 |
| A hybrid sampler for Poisson–Kingman mixture models M Lomeli, S Favaro, YW Teh Advances in Neural Information Processing Systems, 2161-2169, 2015 | 5 | 2015 |
| Sampling and inference for discrete random probability measures in probabilistic programs B Bloem-Reddy, E Mathieu, A Foster, T Rainforth, YW Teh, H Ge, ... NIPS Workshop on Advances in Approximate Bayesian Inference, 2017 | 4 | 2017 |
| On a class of σ-stable Poisson–Kingman models and an effective marginalized sampler S Favaro, M Lomeli, YW Teh Statistics and Computing 25 (1), 67-78, 2015 | 3 | 2015 |
| Masking schemes for universal marginalisers D Gautam, M Lomeli, K Gourgoulias, D Thompson, S Johri Advances in Approximate Bayesian Inference symposium, 2019 | 2 | 2019 |
| Universal marginalizer for amortised inference and embedding of generative models R Walecki, A Buchard, K Gourgoulias, C Hart, M Lomeli, AKW Navarro, ... arXiv preprint arXiv:1811.04727, 2018 | 2 | 2018 |
| RA-DIT: Retrieval-Augmented Dual Instruction Tuning XV Lin, X Chen, M Chen, W Shi, M Lomeli, R James, P Rodriguez, J Kahn, ... arXiv preprint arXiv:2310.01352, 2023 | 1 | 2023 |
Jane Dwivedi-YuMeta AIVerified email at meta.com
