| Challenges and applications of large language models J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu, R McHardy arXiv preprint arXiv:2307.10169, 2023 | 266 | 2023 |
| Causal machine learning: A survey and open problems J Kaddour, A Lynch, Q Liu, MJ Kusner, R Silva arXiv preprint arXiv:2206.15475, 2022 | 122 | 2022 |
| When Do Flat Minima Optimizers Work? J Kaddour, L Liu, R Silva, M Kusner NeurIPS 2022, 2022 | 63 | 2022 |
| Causal Effect Inference for Structured Treatments J Kaddour, Y Zhu, Q Liu, MJ Kusner, R Silva NeurIPS 2021, 2021 | 42 | 2021 |
| Probabilistic Active Meta-Learning J Kaddour, S Sæmundsson, M Deisenroth NeurIPS 2020, 2020 | 41 | 2020 |
| Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging J Kaddour NeurIPS 2022 HITY Workshop, 2022 | 25* | 2022 |
| The minipile challenge for data-efficient language models J Kaddour arXiv preprint arXiv:2304.08442, 2023 | 23 | 2023 |
| Spawrious: A benchmark for fine control of spurious correlation biases A Lynch, GJS Dovonon, J Kaddour, R Silva arXiv preprint arXiv:2303.05470, 2023 | 17 | 2023 |
| No train no gain: Revisiting efficient training algorithms for transformer-based language models J Kaddour, O Key, P Nawrot, P Minervini, MJ Kusner NeurIPS 2023, 2023 | 15 | 2023 |
| SATISFy: Towards a self-learning analyzer for time series forecasting in self-improving systems C Krupitzer, M Pfannemüller, J Kaddour, C Becker 2018 IEEE 3rd International Workshops on Foundations and Applications of …, 2018 | 14 | 2018 |
| Evaluating Self-Supervised Learning for Molecular Graph Embeddings H Wang, J Kaddour, S Liu, J Tang, J Lasenby, Q Liu NeurIPS 2023 Datasets & Benchmarks, 2022 | 12 | 2022 |
| Challenges and applications of large language models. arXiv J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu, R McHardy Preprint posted online 19, 2023 | 11 | 2023 |
| Challenges and applications of large language models (2023) J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu, R McHardy arXiv preprint arXiv:2307.10169 4, 2024 | 9 | 2024 |
| DAG learning on the permutahedron V Zantedeschi, L Franceschi, J Kaddour, M Kusner, V Niculae ICLR 2023, 2023 | 8 | 2023 |
| Challenges and applications of large language models. arXiv 2023 J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu, R McHardy arXiv preprint arXiv:2307.10169, 0 | 8 | |
| Understanding the Effectiveness of Early Weight Averaging for Training Large Language Models S Sanyal, J Kaddour, A Kumar, S Sanghavi arXiv preprint arXiv:2306.03241, 2023 | 7 | 2023 |
| Causal machine learning: A survey and open problems. arXiv 2022 J Kaddour, A Lynch, Q Liu, MJ Kusner, R Silva arXiv preprint arXiv:2206.15475, 2022 | 6 | 2022 |
| Causal machine learning: a survey and open problems (2022) J Kaddour, A Lynch, Q Liu, MJ Kusner, R Silva arXiv preprint arXiv:2206.15475, 0 | 6 | |
| Evaluating the impact of geometric and statistical skews on out-of-distribution generalization performance A Lynch, J Kaddour, R Silva NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022 | 5 | 2022 |
| Early Weight Averaging meets High Learning Rates for LLM Pre-training S Sanyal, AT Neerkaje, J Kaddour, A Kumar NeurIPS 2023 WANT, 2023 | 3 | 2023 |
Robert McHardyAssemblyAIVerified email at assemblyai.com
