Muennighoff, Niklas

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

MTEB: Massive Text Embedding Benchmark

Muennighoff, N., Tazi, N., Magne, L., & Reimers, N. (2023) · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics

Topic ModelingMultimodal Machine Learning Applications

Cited by 548

C-Pack: Packed Resources For General Chinese Embeddings

Xiao, S., Liu, Z., Zhang, P., Muennighoff, N., Lian, D., & Nie, J.-Y. (2024) · Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval

Topic ModelingMultimodal Machine Learning Applications

Cited by 523

C-Pack: Packed Resources For General Chinese Embeddings

Xiao, S., Liu, Z., Zhang, P., Muennighoff, N., Lian, D., & Nie, J.-Y. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 514

Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

Merrill, M. A., Shaw, A. G., Carlini, N., Li, B., Raj, H., Bercovich, I., Shi, L., Shin, J. Y., Walshe, T., Buchanan, E. K., et al. (2026) · arXiv

AI-based Problem Solving and PlanningArtificial Intelligence Applications

Cited by 392

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

OctoPack: Instruction Tuning Code Large Language Models

Muennighoff, N., Liu, Q., Zebaze, A., Zheng, Q., Hui, B., Zhuo, T. Y., Singh, S., Tang, X., von Werra, L., & Longpre, S. (2023) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 245

s1: Simple test-time scaling

Muennighoff, N., Yang, Z., Shi, W., Li, X. L., Fei-Fei, L., Hajishirzi, H., Zettlemoyer, L., Liang, P., Candes, E., & Hashimoto, T. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 76

StarCoder 2 and The Stack v2: The Next Generation

Lozhkov, A., Li, R., Allal, L. B., Cassano, F., Lamy-Poirier, J., Tazi, N., Tang, A., Pykhtar, D., Liu, J., Wei, Y., et al. (2024) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 74

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

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

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

Scaling Data-Constrained Language Models

Muennighoff, N., Rush, A. M., Barak, B., Scao, T. L., Piktus, A., Tazi, N., Pyysalo, S., Wolf, T., & Raffel, C. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 49

Scaling Data-Constrained Language Models

Muennighoff, N., Rush, A., Barak, B., Scao, T. L., Tazi, N., Piktus, A., Pyysalo, S., Wolf, T., & Raffel, C. (2023) · Advances in Neural Information Processing Systems 36

Topic ModelingNatural Language Processing Techniques

Cited by 47

What Language Model to Train if You Have One Million GPU Hours?

Le Scao, T., Wang, T., Hesslow, D., Bekman, S., Bari, M. S., Biderman, S., Elsahar, H., Muennighoff, N., Phang, J., Press, O., et al. (2022) · Findings of the Association for Computational Linguistics: EMNLP 2022

Topic ModelingNatural Language Processing Techniques

Cited by 33

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

KTO: Model Alignment as Prospect Theoretic Optimization

Ethayarajh, K., Xu, W., Muennighoff, N., Jurafsky, D., & Kiela, D. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 29

BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions

Zhuo, T. Y., Vu, M. C., Chim, J., Hu, H., Yu, W., Widyasari, R., Yusuf, I. N. B., Zhan, H., He, J., Paul, I., et al. (2024) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 29

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

OpenHands: An Open Platform for AI Software Developers as Generalist Agents

Wang, X., Li, B., Song, Y., Xu, F. F., Tang, X., Zhuge, M., Pan, J., Song, Y., Li, B., Singh, J., et al. (2024) · arXiv

Software Engineering ResearchArtificial Intelligence Applications

Cited by 24