Lambert, Nathan

OLMo: Accelerating the Science of Language Models

Groeneveld, D., Beltagy, I., Walsh, E., Bhagia, A., Kinney, R., Tafjord, O., Jha, A., Ivison, H., Magnusson, I., Wang, Y., et al. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 70

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models

Deitke, M., Clark, C., Lee, S., Tripathi, R., Yang, Y., Park, J. S., Salehi, M., Muennighoff, N., Lo, K., Soldaini, L., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 67

Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models

Deitke, M., Clark, C., Lee, S., Tripathi, R., Yang, Y., Park, J. S., Salehi, M., Muennighoff, N., Lo, K., Soldaini, L., et al. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 67

Dolma: an open corpus of three trillion tokens for language model pretraining research

Soldaini, L., Kinney, R., Bhagia, A., Schwenk, D., Atkinson, D., Authur, R., Bogin, B., Chandu, K., Dumas, J., Elazar, Y., et al. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 56

On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

Zhang, B., Rajan, R., Pineda, L., Lambert, N., Biedenkapp, A., Chua, K., Hutter, F., & Calandra, R. (2021) · arXiv

Reinforcement Learning in RoboticsMachine Learning and Data Classification

Cited by 53

WildGuard: Open One-stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs

Han, S., Rao, K., Ettinger, A., Jiang, L., Lin, B. Y., Lambert, N., Choi, Y., & Dziri, N. (2024) · Advances in Neural Information Processing Systems 37

Adversarial Robustness in Machine LearningHate Speech and Cyberbullying Detection

Cited by 36

Objective Mismatch in Model-based Reinforcement Learning

Lambert, N., Amos, B., Yadan, O., & Calandra, R. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 33

RewardBench: Evaluating Reward Models for Language Modeling

Lambert, N., Pyatkin, V., Morrison, J., Miranda, L., Lin, B. Y., Chandu, K., Dziri, N., Kumar, S., Zick, T., Choi, Y., et al. (2025) · Findings of the Association for Computational Linguistics: NAACL 2025

Natural Language Processing TechniquesTopic Modeling

Cited by 13

TÜLU 3: Pushing Frontiers in Open Language Model Post-Training

Lambert, N., Morrison, J., Pyatkin, V., Huang, S., Ivison, H., Brahman, F., Miranda, L. J. V., Liu, A., Dziri, N., Lyu, S., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12

A Survey on Data Selection for Language Models

Albalak, A., Elazar, Y., Xie, S. M., Longpre, S., Lambert, N., Wang, X., Muennighoff, N., Hou, B., Pan, L., Jeong, H., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

Soldaini, L., Kinney, R., Bhagia, A., Schwenk, D., Atkinson, D., Authur, R., Bogin, B., Chandu, K., Dumas, J., Elazar, Y., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 10

OLMo: Accelerating the Science of Language Models

Groeneveld, D., Beltagy, I., Walsh, P., Bhagia, A., Kinney, R., Tafjord, O., Jha, A. H., Ivison, H., Magnusson, I., Wang, Y., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 10

Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2

Ivison, H., Wang, Y., Pyatkin, V., Lambert, N., Peters, M., Dasigi, P., Jang, J., Wadden, D., Smith, N. A., Beltagy, I., et al. (2023) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 8

RewardBench: Evaluating Reward Models for Language Modeling

Lambert, N., Pyatkin, V., Morrison, J., Miranda, L., Lin, B. Y., Chandu, K., Dziri, N., Kumar, S., Zick, T., Choi, Y., et al. (2024) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 5

Generalizing Verifiable Instruction Following

Pyatkin, V., Malik, S., Graf, V., Ivison, H., Huang, S., Dasigi, P., Lambert, N., & Hajishirzi, H. (2025) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 4

2 OLMo 2 Furious

OLMo, T., Walsh, P., Soldaini, L., Groeneveld, D., Lo, K., Arora, S., Bhagia, A., Gu, Y., Huang, S., Jordan, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

Spurious Rewards: Rethinking Training Signals in RLVR

Shao, R., Li, S. S., Xin, R., Geng, S., Wang, Y., Oh, S., Du, S. S., Lambert, N., Min, S., Krishna, R., et al. (2025) · arXiv

Reinforcement Learning in RoboticsTopic Modeling

Cited by 1

RewardBench 2: Advancing Reward Model Evaluation

Malik, S., Pyatkin, V., Land, S., Morrison, J., Smith, N. A., Hajishirzi, H., & Lambert, N. (2025) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 1