Muennighoff, Niklas

Generative Representational Instruction Tuning

Muennighoff, N., Su, H., Wang, L., Yang, N., Wei, F., Yu, T., Singh, A., & Kiela, D. (2024) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 16

Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence

Peng, B., Goldstein, D., Anthony, Q., Albalak, A., Alcaide, E., Biderman, S., Cheah, E., Du, X., Ferdinan, T., Hou, H., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 13

s1: Simple test-time scaling

Muennighoff, N., Yang, Z., Shi, W., Li, X. L., Fei-Fei, L., Hajishirzi, H., Zettlemoyer, L., Liang, P., Candès, E., & Hashimoto, T. (2025) · 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

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

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

Scao, T. L., Wang, T., Hesslow, D., Saulnier, L., Bekman, S., Bari, M. S., Biderman, S., Elsahar, H., Muennighoff, N., Phang, J., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 9

Language models scale reliably with over-training and on downstream tasks

Gadre, S. Y., Smyrnis, G., Shankar, V., Gururangan, S., Wortsman, M., Shao, R., Mercat, J., Fang, A., Li, J., Keh, S., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 5

SWE-bench Multimodal: Do AI Systems Generalize to Visual Software Domains?

Yang, J., Jimenez, C. E., Zhang, A. L., Lieret, K., Yang, J., Wu, X., Press, O., Muennighoff, N., Synnaeve, G., Narasimhan, K. R., et al. (2024) · arXiv

Software Engineering ResearchSoftware Testing and Debugging Techniques

Cited by 3

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

OpenThoughts: Data Recipes for Reasoning Models

Guha, E., Marten, R., Keh, S., Raoof, N., Smyrnis, G., Bansal, H., Nezhurina, M., Mercat, J., Vu, T., Sprague, Z., et al. (2025) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 1

Composer 2 Technical Report

Research, C., :, Chan, A., Shalaby, A., Wettig, A., Sanger, A., Zhai, A., Ajay, A., Nair, A., Snell, C., et al. (2026) · arXiv

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 1