| Zephyr: Direct distillation of lm alignment L Tunstall, E Beeching, N Lambert, N Rajani, K Rasul, Y Belkada, ... arXiv preprint arXiv:2310.16944, 2023 | 544 | 2023 |
| [Github] Diffusers: State-of-the-art diffusion models P von Platen, S Patil, A Lozhkov, P Cuenca, N Lambert, K Rasul, ... https://github.com/huggingface/diffusers, 2022 | 480* | 2022 |
| Open LLM Leaderboard E Beeching, C Fourrier, N Habib, S Han, N Lambert, N Rajani, ... URL https://huggingface. co/spaces/HuggingFaceH4/open_llm_leaderboard, 2023 | 334 | 2023 |
| Olmo: Accelerating the science of language models D Groeneveld, I Beltagy, P Walsh, A Bhagia, R Kinney, O Tafjord, AH Jha, ... arXiv preprint arXiv:2402.00838, 2024 | 268* | 2024 |
| [Github] Trl: Transformer reinforcement learning L von Werra, Y Belkada, L Tunstall, E Beeching, T Thrush, N Lambert https://github.com/lvwerra/trl, 2020 | 221* | 2020 |
| Dolma: An open corpus of three trillion tokens for language model pretraining research L Soldaini, R Kinney, A Bhagia, D Schwenk, D Atkinson, R Authur, ... arXiv preprint arXiv:2402.00159, 2024 | 197* | 2024 |
| Low Level Control of a Quadrotor with Deep Model-Based Reinforcement Learning N Lambert, DS Drew, J Yaconelli, R Calandra, S Levine, KSJ Pister IEEE Robotics and Automation Letters 4 (4), 4224-4230, 2019 | 197 | 2019 |
| Rewardbench: Evaluating reward models for language modeling N Lambert, V Pyatkin, J Morrison, LJ Miranda, BY Lin, K Chandu, N Dziri, ... arXiv preprint arXiv:2403.13787, 2024 | 194 | 2024 |
| Camels in a changing climate: Enhancing lm adaptation with tulu 2 H Ivison, Y Wang, V Pyatkin, N Lambert, M Peters, P Dasigi, J Jang, ... arXiv preprint arXiv:2311.10702, 2023 | 178 | 2023 |
| On the importance of hyperparameter optimization for model-based reinforcement learning B Zhang, R Rajan, L Pineda, N Lambert, A Biedenkapp, K Chua, F Hutter, ... International Conference on Artificial Intelligence and Statistics, 4015-4023, 2021 | 135 | 2021 |
| [Blog] Illustrating reinforcement learning from human feedback (RLHF) N Lambert, L Castricato, L von Werra, A Havrilla https://hf.co/blog/rlhf, 2022 | 131* | 2022 |
| Objective Mismatch in Model-based Reinforcement Learning N Lambert, B Amos, O Yadan, R Calandra Learning for Dynamics and Control (L4DC), 2020 | 115 | 2020 |
| A survey on data selection for language models A Albalak, Y Elazar, SM Xie, S Longpre, N Lambert, X Wang, ... arXiv preprint arXiv:2402.16827, 2024 | 94 | 2024 |
| Toward controlled flight of the ionocraft: a flying microrobot using electrohydrodynamic thrust with onboard sensing and no moving parts D Drew, N Lambert, C Schindler, K Pister IEEE Robotics and Automation Letters 3 (4), 2807-2813, 2018 | 88 | 2018 |
| Molmo and pixmo: Open weights and open data for state-of-the-art multimodal models M Deitke, C Clark, S Lee, R Tripathi, Y Yang, JS Park, M Salehi, ... arXiv preprint arXiv:2409.17146, 2024 | 78* | 2024 |
| Mbrl-lib: A modular library for model-based reinforcement learning L Pineda, B Amos, A Zhang, NO Lambert, R Calandra arXiv preprint arXiv:2104.10159, 2021 | 57 | 2021 |
| The Alignment Handbook L Tunstall, E Beeching, N Lambert, N Rajani, S Huang, K Rasul, ... URL https://github. com/huggingface/alignment-handbook, 2023 | 55 | 2023 |
| Learning generalizable locomotion skills with hierarchical reinforcement learning T Li, N Lambert, R Calandra, F Meier, A Rai IEEE International Conference on Robotics and Automation (ICRA), 413-419, 2020 | 50 | 2020 |
| The challenges of exploration for offline reinforcement learning N Lambert, M Wulfmeier, W Whitney, A Byravan, M Bloesch, V Dasagi, ... arXiv preprint arXiv:2201.11861, 2022 | 45 | 2022 |
| Tülu 3: Pushing Frontiers in Open Language Model Post-Training N Lambert, J Morrison, V Pyatkin, S Huang, H Ivison, F Brahman, ... arXiv preprint arXiv:2411.15124, 2024 | 44* | 2024 |
Valentina PyatkinAllen Institute for AI & University of WashingtonВерификована је имејл адреса на allenai.org
