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Generate rather than Retrieve: Large Language Models are Strong Context Generators.

W. Yu, D. Iter, S. Wang, Y. Xu, M. Ju, S. Sanyal, C. Zhu, M. Zeng, and M. Jiang. ICLR, OpenReview.net, (2023)

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Dan Brüllmann

Dan Tidten

Dan Bauer

Dan Wang

Marius Dan

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InheritSumm: A General, Versatile and Compact Summarizer by Distilling from GPT.Y. Xu, R. Xu, D. Iter, Y. Liu, S. Wang, C. Zhu, and M. Zeng. EMNLP (Findings), page 13879-13892. Association for Computational Linguistics, (2023)Identifying content for planned events across social media sites.H. Becker, D. Iter, M. Naaman, and L. Gravano. WSDM, page 533-542. ACM, (2012)Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models.D. Iter, K. Guu, L. Lansing, and D. Jurafsky. ACL, page 4859-4870. Association for Computational Linguistics, (2020)Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference.W. Held, D. Iter, and D. Jurafsky. EMNLP (1), page 1406-1417. Association for Computational Linguistics, (2021)LMGQS: A Large-scale Dataset for Query-focused Summarization.R. Xu, S. Wang, Y. Liu, S. Wang, Y. Xu, D. Iter, P. He, C. Zhu, and M. Zeng. EMNLP (Findings), page 14764-14776. Association for Computational Linguistics, (2023)Generate rather than Retrieve: Large Language Models are Strong Context Generators.W. Yu, D. Iter, S. Wang, Y. Xu, M. Ju, S. Sanyal, C. Zhu, M. Zeng, and M. Jiang. ICLR, OpenReview.net, (2023)How Does In-Context Learning Help Prompt Tuning?S. Sun, Y. Liu, D. Iter, C. Zhu, and M. Iyyer. EACL (Findings), page 156-165. Association for Computational Linguistics, (2024)Automatic Identification and Presentation of Twitter Content for Planned Events.H. Becker, F. Chen, D. Iter, M. Naaman, and L. Gravano. ICWSM, The AAAI Press, (2011)The Trade-offs of Domain Adaptation for Neural Language Models.D. Grangier, and D. Iter. ACL (1), page 3802-3813. Association for Computational Linguistics, (2022)In-Context Demonstration Selection with Cross Entropy Difference.D. Iter, R. Pryzant, R. Xu, S. Wang, Y. Liu, Y. Xu, and C. Zhu. EMNLP (Findings), page 1150-1162. Association for Computational Linguistics, (2023)

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Disambiguation of "Iter, Dan"

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Generate rather than Retrieve: Large Language Models are Strong Context Generators.

Please choose a person to relate this publication to

Dan Brüllmann

Dan Tidten

Dan Bauer

Dan Wang

Marius Dan

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Iter, Dan"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Generate rather than Retrieve: Large Language Models are Strong Context Generators.

Please choose a person to relate this publication to

Dan Brüllmann

Dan Tidten

Dan Bauer

Dan Wang

Marius Dan

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Generate rather than Retrieve: Large Language Models are Strong Context Generators.