The Trade-offs of Domain Adaptation for Neural Language Models von Grangier, David, Iter, Dan

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On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation von Iter, Dan, Grangier, David

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Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference von Held, William, Iter, Dan, Jurafsky, Dan

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How Does In-Context Learning Help Prompt Tuning? von Sun, Simeng, Liu, Yang, Iter, Dan, Zhu, Chenguang, Iyyer, Mohit

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The Trade-offs of Domain Adaptation for Neural Language Models von Grangier, David, Iter, Dan

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On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation von Iter, Dan, Grangier, David

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In-Context Demonstration Selection with Cross Entropy Difference von Iter, Dan, Pryzant, Reid, Xu, Ruochen, Wang, Shuohang, Liu, Yang, Xu, Yichong, Zhu, Chenguang

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InheritSumm: A General, Versatile and Compact Summarizer by Distilling from GPT von Xu, Yichong, Xu, Ruochen, Iter, Dan, Liu, Yang, Wang, Shuohang, Zhu, Chenguang, Zeng, Michael

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LMGQS: A Large-scale Dataset for Query-focused Summarization von Xu, Ruochen, Wang, Song, Liu, Yang, Wang, Shuohang, Xu, Yichong, Iter, Dan, Zhu, Chenguang, Zeng, Michael

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Automatic Prompt Optimization with "Gradient Descent" and Beam Search von Pryzant, Reid, Iter, Dan, Li, Jerry, Lee, Yin Tat, Zhu, Chenguang, Zeng, Michael

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G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment von Liu, Yang, Iter, Dan, Xu, Yichong, Wang, Shuohang, Xu, Ruochen, Zhu, Chenguang

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Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models von Zhang, Zhihan, Wang, Shuohang, Yu, Wenhao, Xu, Yichong, Iter, Dan, Zeng, Qingkai, Liu, Yang, Zhu, Chenguang, Jiang, Meng

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The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions von Ouyang, Siru, Wang, Shuohang, Liu, Yang, Zhong, Ming, Jiao, Yizhu, Iter, Dan, Pryzant, Reid, Zhu, Chenguang, Ji, Heng, Han, Jiawei

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Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models von Iter, Dan, Guu, Kelvin, Lansing, Larry, Jurafsky, Dan

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Generate rather than Retrieve: Large Language Models are Strong Context Generators von Yu, Wenhao, Iter, Dan, Wang, Shuohang, Xu, Yichong, Ju, Mingxuan, Sanyal, Soumya, Zhu, Chenguang, Zeng, Michael, Jiang, Meng

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Identifying entity attribute relations von Iter, Dan, Yu, Xiao, Li, Fangtao

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How Does In-Context Learning Help Prompt Tuning? von Sun, Simeng, Liu, Yang, Iter, Dan, Zhu, Chenguang, Iyyer, Mohit

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NATURAL LANGUAGE TRAINING AND/OR AUGMENTATION WITH LARGE LANGUAGE MODELS von WANG, Shuohang, ITER, Dan, ZENG, Nanshan, XU, Yichong, LIU, Yang, ZHU, Chenguang, SHARMA, Hiteshi

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NATURAL LANGUAGE TRAINING AND/OR AUGMENTATION WITH LARGE LANGUAGE MODELS von WANG, Shuohang, ITER, Dan, ZENG, Nanshan, XU, Yichong, LIU, Yang, ZHU, Chenguang, SHARMA, Hiteshi

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IDENTIFYING ENTITY ATTRIBUTE RELATIONS von Iter, Dan, Yu, Xiao, Li, Fangtao

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