( en | de | ru )

 

Disambiguation

From post

копироватьудалитьдобавить публикацию в буфер
Don't Stop Pretraining: Adapt Language Models to Domains and Tasks

, , , , , , и . (2020)cite arxiv:2004.10964Comment: ACL 2020.

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

No persons found for author name Gururangan, Suchin
add a person with the name Gururangan, Suchin
 

Другие публикации лиц с тем же именем

Scaling Expert Language Models with Unsupervised Domain Discovery., , , , , , и . CoRR, (2023)LESS: Selecting Influential Data for Targeted Instruction Tuning., , , , и . CoRR, (2024)lo-fi: distributed fine-tuning without communication., , , , , , и . CoRR, (2022)M2D2: A Massively Multi-Domain Language Modeling Dataset., , , и . EMNLP, стр. 964-975. Association for Computational Linguistics, (2022)Time is Encoded in the Weights of Finetuned Language Models., , и . CoRR, (2023)Language models scale reliably with over-training and on downstream tasks., , , , , , , , , и 13 other автор(ы). CoRR, (2024)AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters., , , , , , и . CoRR, (2024)Show Your Work: Improved Reporting of Experimental Results., , , , и . EMNLP/IJCNLP (1), стр. 2185-2194. Association for Computational Linguistics, (2019)Information Flow Control in Machine Learning through Modular Model Architecture., , , , , , , , , и . CoRR, (2023)DEMix Layers: Disentangling Domains for Modular Language Modeling., , , , и . NAACL-HLT, стр. 5557-5576. Association for Computational Linguistics, (2022)