Dodge, Jesse

Green AI

Schwartz, R., Dodge, J., Smith, N. A., & Etzioni, O. (2020) · Communications of the ACM

Green IT and SustainabilityEnergy Efficiency in Computing

Cited by 1,647

Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping

Dodge, J., Ilharco, G., Schwartz, R., Farhadi, A., Hajishirzi, H., & Smith, N. (2020) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 412

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

Measuring the Carbon Intensity of AI in Cloud Instances

Dodge, J., Prewitt, T., Tachet des Combes, R., Odmark, E., Schwartz, R., Strubell, E., Luccioni, A. S., Smith, N. A., DeCario, N., & Buchanan, W. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Green IT and SustainabilityEnergy Efficiency in Computing

Cited by 257

Show Your Work: Improved Reporting of Experimental Results

Dodge, J., Gururangan, S., Card, D., Schwartz, R., & Smith, N. A. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Academic Writing and PublishingScientific Computing and Data Management

Cited by 233

Competency Problems: On Finding and Removing Artifacts in Language Data

Gardner, M., Merrill, W., Dodge, J., Peters, M., Ross, A., Singh, S., & Smith, N. A. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 81

Data Governance in the Age of Large-Scale Data-Driven Language Technology

Jernite, Y., Nguyen, H., Biderman, S., Rogers, A., Masoud, M., Danchev, V., Tan, S., Luccioni, A. S., Subramani, N., Johnson, I., et al. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 75

Green AI

Schwartz, R., Dodge, J., Smith, N. A., & Etzioni, O. (2019) · arXiv

Green IT and SustainabilityEnergy Efficiency in Computing

Cited by 73

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

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

AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models

Chronopoulou, A., Peters, M., Fraser, A., & Dodge, J. (2023) · Findings of the Association for Computational Linguistics: EACL 2023

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 30

Brittlebench: Quantifying LLM robustness via prompt sensitivity

Romanou, A., Ibrahim, M., Ross, C., Oktar, K., Shaib, C., Bell, S. J., Ovalle, A., Bosselut, A., Dodge, J., Sinha, K., et al. (2026) · arXiv

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 24

Show Your Work: Improved Reporting of Experimental Results

Dodge, J., Gururangan, S., Card, D., Schwartz, R., & Smith, N. A. (2019) · arXiv

Machine Learning and Data ClassificationNatural Language Processing Techniques

Cited by 22

Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved With Text

Zhu, W., Hessel, J., Awadalla, A., Gadre, S. Y., Dodge, J., Fang, A., Yu, Y., Schmidt, L., Wang, W. Y., & Choi, Y. (2023) · arXiv

Multimodal Machine Learning ApplicationsNatural Language Processing Techniques

Cited by 21

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

ML Reproducibility Challenge 2022

Sinha, K., Bleeker, M., Bhargav, S., Forde, J. Z., Raparthy, S. C., Dodge, J., Pineau, J., & Stojnic, R. (2023) · Zenodo

Scientific Computing and Data ManagementMachine Learning and Data Classification

Cited by 10

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

Language Models Hallucinate, but May Excel at Fact Verification

Guan, J., Dodge, J., Wadden, D., Huang, M., & Peng, H. (2023) · arXiv

Topic ModelingMisinformation and Its Impacts

Cited by 3

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

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

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation

Heineman, D., Hofmann, V., Magnusson, I., Gu, Y., Smith, N. A., Hajishirzi, H., Lo, K., & Dodge, J. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0