| Unsupervised learning of sentence embeddings using compositional n-gram features M Pagliardini, P Gupta, M Jaggi NAACL-HLT, 2018, 2017 | 964 | 2017 |
| Meditron-70b: Scaling medical pretraining for large language models Z Chen, AH Cano, A Romanou, A Bonnet, K Matoba, F Salvi, ... arXiv preprint arXiv:2311.16079, 2023 | 291 | 2023 |
| Agree to disagree: Diversity through disagreement for better transferability M Pagliardini, M Jaggi, F Fleuret, SP Karimireddy ICLR 2023, 2022 | 80 | 2022 |
| Better word embeddings by disentangling contextual n-gram information P Gupta, M Pagliardini, M Jaggi NAACL-HLT, 2019, 2019 | 52 | 2019 |
| Taming gans with lookahead T Chavdarova, M Pagliardini, SU Stich, M Jaggi, F Fleuret ICLR 2021, 2020 | 41* | 2020 |
| Fast attention over long sequences with dynamic sparse flash attention M Pagliardini, D Paliotta, M Jaggi, F Fleuret Advances in Neural Information Processing Systems 36, 59808-59831, 2023 | 35* | 2023 |
| Doge: Domain reweighting with generalization estimation S Fan, M Pagliardini, M Jaggi arXiv preprint arXiv:2310.15393, 2023 | 29 | 2023 |
| The peril of popular deep learning uncertainty estimation methods Y Liu, M Pagliardini, T Chavdarova, SU Stich Bayesian Deep Learning workshop, at NeurIPS 2021, 2021 | 21 | 2021 |
| Meditron-70b: Scaling medical pretraining for large language models, 2023 Z Chen, AH Cano, A Romanou, A Bonnet, K Matoba, F Salvi, ... URL https://arxiv. org/abs/2311.16079, 2023 | 16 | 2023 |
| Unsupervised learning of sentence embeddings using compositional n-gram features (2017) M Pagliardini, P Gupta, M Jaggi arXiv preprint arXiv:1703.02507, 2017 | 13 | 2017 |
| The ademamix optimizer: Better, faster, older M Pagliardini, P Ablin, D Grangier arXiv preprint arXiv:2409.03137, 2024 | 9 | 2024 |
| Denseformer: Enhancing information flow in transformers via depth weighted averaging M Pagliardini, A Mohtashami, F Fleuret, M Jaggi Advances in Neural Information Processing Systems 37, 136479-136508, 2024 | 6 | 2024 |
| A primal-dual approach to solving variational inequalities with general constraints T Chavdarova, T Yang, M Pagliardini, MI Jordan arXiv preprint arXiv:2210.15659, 2022 | 5* | 2022 |
| Meditron: Open medical foundation models adapted for clinical practice A Bosselut, Z Chen, A Romanou, A Bonnet, A Hernández-Cano, ... | 4 | 2024 |
| Cotformer: More tokens with attention make up for less depth A Mohtashami, M Pagliardini, M Jaggi Workshop on Advancing Neural Network Training: Computational Efficiency …, 2023 | 3 | 2023 |
| Improving generalization via uncertainty driven perturbations M Pagliardini, G Manunza, M Jaggi, MI Jordan, T Chavdarova arXiv preprint arXiv:2202.05737, 2022 | 3 | 2022 |
| Diversity through disagreement for better transferability M Pagliardini, M Jaggi, F Fleuret, SP Karimireddy NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022 | 2 | 2022 |
| Thinking slow, fast: Scaling inference compute with distilled reasoners D Paliotta, J Wang, M Pagliardini, KY Li, A Bick, JZ Kolter, A Gu, F Fleuret, ... arXiv preprint arXiv:2502.20339, 2025 | 1 | 2025 |
| Leveraging the true depth of LLMs RC González, D Paliotta, M Pagliardini, M Jaggi, F Fleuret arXiv preprint arXiv:2502.02790, 2025 | 1 | 2025 |
| Fast causal attention with dynamic sparsity D Paliotta, M Pagliardini, M Jaggi, F Fleuret Workshop on Efficient Systems for Foundation Models@ ICML2023, 2023 | 1 | 2023 |
Martin JaggiEPFLVerified email at epfl.ch
