Jesse Dodge

Allen Institute — United States

Computer Science · Physical Sciences

24h-index5.0kcitations88works5.32yr avg
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Research Topics

Natural Language Processing Techniques(52), Topic Modeling(46), Machine Learning and Data Classification(8), Speech Recognition and Synthesis(6), Multimodal Machine Learning Applications(6)

Publications88 total

Evaluating the Social Impact of Generative AI Systems
Oxford University Press eBooks·2025· 1 cited
Fluid Language Model Benchmarking
arXiv (Cornell University)·2025Open Access
Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation
arXiv (Cornell University)·2025Open Access
SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks
ArXiv.org·2025Open Access
DataDecide: How to Predict Best Pretraining Data with Small Experiments
arXiv (Cornell University)·2025Open Access
OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens
arXiv (Cornell University)·2025Open Access
Efficient Methods for Natural Language Processing: A Survey
UNC Libraries·2025Open Access
Investigating machine moral judgement through the Delphi experiment
Nature Machine Intelligence·2025· 16 citedOpen Access
OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens
2025· 1 citedOpen Access
OLMES: A Standard for Language Model Evaluations
2025· 2 citedOpen Access
The Generative AI Ethics Playbook
arXiv (Cornell University)·2024Open Access
Establishing Task Scaling Laws via Compute-Efficient Model Ladders
arXiv (Cornell University)·2024Open Access
Scalable Data Ablation Approximations for Language Models through Modular Training and Merging
arXiv (Cornell University)·2024Open Access
Merge to Learn: Efficiently Adding Skills to Language Models with Model Merging
arXiv (Cornell University)·2024Open Access
OLMES: A Standard for Language Model Evaluations
arXiv (Cornell University)·2024Open Access
OLMo: Accelerating the Science of Language Models
arXiv (Cornell University)·2024· 9 citedOpen Access
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
arXiv (Cornell University)·2024· 8 citedOpen Access
AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters
arXiv (Cornell University)·2024· 2 citedOpen Access
Language Models Hallucinate, but May Excel at Fact Verification
2024· 13 citedOpen Access
Scalable Data Ablation Approximations for Language Models through Modular Training and Merging
2024· 2 citedOpen Access
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Frequent Co-authors

Noah A. Smith(18), Roy Schwartz(13), Margaret Mitchell(10), Emma Strubell(8), Kyle Lo(7), Matthew E. Peters(7), Dirk Groeneveld(7), Alexandra Sasha Luccioni(6), Iz Beltagy(6), Hannaneh Hajishirzi(6), Nishant Subramani(6), Oren Etzioni(5), Hal Daumé(5), Niklas Muennighoff(5), Gabriel Ilharco(5), Yejin Choi(5), Luke Zettlemoyer(5), Maarten Sap(5), Kota Yamaguchi(4), Karl Stratos(4)