Groeneveld, Dirk
Allen Institute for Artificial Intelligence
12 papers on CoChatORCID 0000-0002-8274-768X
Most cited papers
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Construction of the Literature Graph in Semantic Scholar
Ammar, W., Groeneveld, D., Bhagavatula, C., Beltagy, I., Crawford, M., Downey, D., Dunkelberger, J., Elgohary, A., Feldman, S., Ha, V., et al. (2018) · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers)
scientometrics and bibliometrics researchTopic Modeling
Cited by 358
- Verified
Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus
Dodge, J., Sap, M., Marasović, A., Agnew, W., Ilharco, G., Groeneveld, D., Mitchell, M., & Gardner, M. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Natural Language Processing TechniquesTopic Modeling
Cited by 306
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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
- Verified
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
- Verified
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
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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
- Verified
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
- Verified
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
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What's In My Big Data?
Elazar, Y., Bhagia, A., Magnusson, I., Ravichander, A., Schwenk, D., Suhr, A., Walsh, P., Groeneveld, D., Soldaini, L., Singh, S., et al. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 9
- Verified
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
- Verified
Paloma: A Benchmark for Evaluating Language Model Fit
Magnusson, I., Bhagia, A., Hofmann, V., Soldaini, L., Jha, A. H., Tafjord, O., Schwenk, D., Walsh, E. P., Elazar, Y., Lo, K., et al. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 1
- Verified
DataDecide: How to Predict Best Pretraining Data with Small Experiments
Magnusson, I., Tai, N., Bogin, B., Heineman, D., Hwang, J. D., Soldaini, L., Bhagia, A., Liu, J., Groeneveld, D., Tafjord, O., et al. (2025) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 1
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