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Nathan Lambert
Nathan Lambert
Research Scientist, Allen AI
Verified email at allenai.org - Homepage
Title
Cited by
Cited by
Year
Zephyr: Direct distillation of lm alignment
L Tunstall, E Beeching, N Lambert, N Rajani, K Rasul, Y Belkada, ...
arXiv preprint arXiv:2310.16944, 2023
4332023
[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
403*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
289*2023
[Github] Trl: Transformer reinforcement learning
L von Werra, Y Belkada, L Tunstall, E Beeching, T Thrush, N Lambert
https://github.com/lvwerra/trl, 2020
191*2020
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
1852019
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
176*2024
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
133*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
1292023
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
1282021
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
117*2024
[Blog] Illustrating reinforcement learning from human feedback (RLHF)
N Lambert, L Castricato, L von Werra, A Havrilla
https://hf.co/blog/rlhf, 2022
113*2022
Objective Mismatch in Model-based Reinforcement Learning
N Lambert, B Amos, O Yadan, R Calandra
Learning for Dynamics and Control (L4DC), 2020
1042020
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
832018
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
652024
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
522021
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
482020
The Alignment Handbook
L Tunstall, E Beeching, N Lambert, N Rajani, S Huang, K Rasul, ...
URL https://github. com/huggingface/alignment-handbook, 2023
452023
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
402022
Reward reports for reinforcement learning
TK Gilbert, N Lambert, S Dean, T Zick, A Snoswell, S Mehta
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 84-130, 2023
382023
[HuggingFace] H4 Stack Exchange Preference Dataset
N Lambert, NR Lewis Tunstall, T Thrush
https://huggingface.co/datasets/HuggingFaceH4/stack-exchange-preferences, 2023
36*2023
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