Mistral 7B AQ Jiang, A Sablayrolles, A Mensch, C Bamford, DS Chaplot, D Casas, ... arXiv preprint arXiv:2310.06825, 2023 | 1148* | 2023 |
Mixtral of experts AQ Jiang, A Sablayrolles, A Roux, A Mensch, B Savary, C Bamford, ... arXiv preprint arXiv:2401.04088, 2024 | 277 | 2024 |
Autoformalization with large language models Y Wu, AQ Jiang, W Li, MN Rabe, C Staats, M Jamnik, C Szegedy NeurIPS 2022, 2022 | 107 | 2022 |
Llemma: An open language model for mathematics Z Azerbayev, H Schoelkopf, K Paster, MD Santos, S McAleer, AQ Jiang, ... arXiv preprint arXiv:2310.10631, 2023 | 83 | 2023 |
Draft, sketch, and prove: Guiding formal theorem provers with informal proofs AQ Jiang, S Welleck, JP Zhou, W Li, J Liu, M Jamnik, T Lacroix, Y Wu, ... arXiv preprint arXiv:2210.12283, 2022 | 82 | 2022 |
Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers AQ Jiang, W Li, S Tworkowski, K Czechowski, T Odrzygóźdź, P Miłoś, ... NeurIPS 2022, 2022 | 53 | 2022 |
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving Y Wu, AQ Jiang, J Ba, R Grosse International Conference on Learning Representations (ICLR 2021), 2021 | 45 | 2021 |
LISA: Language models of isabelle proofs AQ Jiang, W Li, JM Han, Y Wu 6th Conference on Artificial Intelligence and Theorem Proving, 2021 | 38 | 2021 |
Magnushammer: A transformer-based approach to premise selection M Mikuła, S Antoniak, S Tworkowski, AQ Jiang, JP Zhou, C Szegedy, ... arXiv preprint arXiv:2303.04488, 2023 | 18* | 2023 |
Evaluating language models for mathematics through interactions KM Collins, AQ Jiang, S Frieder, L Wong, M Zilka, U Bhatt, T Lukasiewicz, ... arXiv preprint arXiv:2306.01694, 2023 | 17 | 2023 |
Multilingual mathematical autoformalization AQ Jiang, W Li, M Jamnik arXiv preprint arXiv:2311.03755, 2023 | 5 | 2023 |
Learning plausible and useful conjectures AQ Jiang, W Li, M Jamnik 7th Conference on Artificial Intelligence and Theorem Proving, 2022 | 1* | 2022 |
Can Network Flatness Explain the Training Speed-Generalisation Connection? AQ Jiang, L Schut, C Lyle, Y Gal Bayesian Deep Learning Workshop at the Thirty-fifth Conference on Neural …, 2021 | | 2021 |