| Toolformer: Language models can teach themselves to use tools T Schick, J Dwivedi-Yu, R Dessì, R Raileanu, M Lomeli, E Hambro, ... Advances in Neural Information Processing Systems 36, 68539-68551, 2023 | 1467 | 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 1 (2), 4, 2022 | 672* | 2022 |
| Augmented language models: a survey G Mialon, R Dessì, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ... arXiv preprint arXiv:2302.07842, 2023 | 504 | 2023 |
| The faiss library M Douze, A Guzhva, C Deng, J Johnson, G Szilvasy, PE Mazaré, ... arXiv preprint arXiv:2401.08281, 2024 | 368* | 2024 |
| 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 | 107 | 2023 |
| Kernel Adaptive Metropolis–Hastings. D Sejdinovic, H Strathmann, M Lomeli-Garcia, C Andrieu, A Gretton ICML, 1665-1673, 2014 | 62 | 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 | 59 | 2021 |
| Facebook’s cyber–cyber and cyber–physical digital twins J Ahlgren, K Bojarczuk, S Drossopoulou, I Dvortsova, J George, ... Proceedings of the 25th International Conference on Evaluation and …, 2021 | 40 | 2021 |
| General latent feature models for heterogeneous datasets I Valera, MF Pradier, M Lomeli, Z Ghahramani Journal of Machine Learning Research 21 (100), 1-49, 2020 | 28 | 2020 |
| 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 | 23 | 2023 |
| Antithetic and Monte Carlo kernel estimators for partial rankings M Lomeli, M Rowland, A Gretton, Z Ghahramani Statistics and Computing 29, 1127-1147, 2019 | 23 | 2019 |
| A marginal sampler for σ-stable Poisson–Kingman mixture models M Lomelí, S Favaro, YW Teh Journal of Computational and Graphical Statistics, 2015 | 23 | 2015 |
| 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 | 20 | 2022 |
| 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 | 18 | 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 |
| In-context pretraining: Language modeling beyond document boundaries W Shi, S Min, M Lomeli, C Zhou, M Li, G Szilvasy, R James, XV Lin, ... arXiv preprint arXiv:2310.10638, 2023 | 7 | 2023 |
| 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 | 7 | 2021 |
| TOOLVERIFIER: Generalization to New Tools via Self-Verification D Mekala, J Weston, J Lanchantin, R Raileanu, M Lomeli, J Shang, ... arXiv preprint arXiv:2402.14158, 2024 | 6 | 2024 |
| A hybrid sampler for Poisson–Kingman mixture models M Lomeli, S Favaro, YW Teh Advances in Neural Information Processing Systems, 2161-2169, 2015 | 6 | 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, ... Proc. NeurIPS 2017 Workshop on Advances in Approximate Bayesian Inference, 2017 | 4 | 2017 |
Jane YuMeta AI在 meta.com 的电子邮件经过验证
