Schoelkopf, Hailey

Crosslingual Generalization through Multitask Finetuning

Muennighoff, N., Wang, T., Sutawika, L., Roberts, A., Biderman, S., Le Scao, T., Bari, M. S., Shen, S., Yong, Z. X., Schoelkopf, H., et al. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 361

StarCoder: may the source be with you!

Li, R., Allal, L. B., Zi, Y., Muennighoff, N., Kocetkov, D., Mou, C., Marone, M., Akiki, C., Li, J., Chim, J., et al. (2023) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 261

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling

Biderman, S., Schoelkopf, H., Anthony, Q., Bradley, H., O'Brien, K., Hallahan, E., Khan, M. A., Purohit, S., Prashanth, U. S., Raff, E., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 160

Humanity's Last Exam

Phan, L., Gatti, A., Han, Z., Li, N., Hu, J., Zhang, H., Zhang, C. B. C., Shaaban, M., Ling, J., Shi, S., et al. (2025) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 65

SantaCoder: don't reach for the stars!

Allal, L. B., Li, R., Kocetkov, D., Mou, C., Akiki, C., Ferrandis, C. M., Muennighoff, N., Mishra, M., Gu, A., Dey, M., et al. (2023) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 61

FOLIO: Natural Language Reasoning with First-Order Logic

Han, S., Schoelkopf, H., Zhao, Y., Qi, Z., Riddell, M., Zhou, W., Coady, J., Peng, D., Qiao, Y., Benson, L., et al. (2022) · arXiv

Topic ModelingLogic, Reasoning, and Knowledge

Cited by 35

BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting

Yong, Z. X., Schoelkopf, H., Muennighoff, N., Aji, A. F., Adelani, D. I., Almubarak, K., Bari, M. S., Sutawika, L., Kasai, J., Baruwa, A., et al. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 30

Crosslingual Generalization through Multitask Finetuning

Muennighoff, N., Wang, T., Sutawika, L., Roberts, A., Biderman, S., Scao, T. L., Bari, M. S., Shen, S., Yong, Z.-X., Schoelkopf, H., et al. (2022) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 29

Lessons from the Trenches on Reproducible Evaluation of Language Models

Biderman, S., Schoelkopf, H., Sutawika, L., Gao, L., Tow, J., Abbasi, B., Aji, A. F., Ammanamanchi, P. S., Black, S., Clive, J., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 9

From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models

Welleck, S., Bertsch, A., Finlayson, M., Schoelkopf, H., Xie, A., Neubig, G., Kulikov, I., & Harchaoui, Z. (2024) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 3

Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?

Schaeffer, R., Schoelkopf, H., Miranda, B., Mukobi, G., Madan, V., Ibrahim, A., Bradley, H., Biderman, S., & Koyejo, S. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting

Yong, Z.-X., Schoelkopf, H., Muennighoff, N., Aji, A. F., Adelani, D. I., Almubarak, K., Bari, M. S., Sutawika, L., Kasai, J., Baruwa, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2