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2020 – today
- 2023
[c10]Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang:
Generate rather than Retrieve: Large Language Models are Strong Context Generators. ICLR 2023- [i14]Simeng Sun, Yang Liu, Dan Iter, Chenguang Zhu, Mohit Iyyer:
How Does In-Context Learning Help Prompt Tuning? CoRR abs/2302.11521 (2023) - [i13]Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, Chenguang Zhu:
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment. CoRR abs/2303.16634 (2023) - [i12]Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, Michael Zeng:
Automatic Prompt Optimization with "Gradient Descent" and Beam Search. CoRR abs/2305.03495 (2023) - [i11]Yichong Xu, Ruochen Xu, Dan Iter, Yang Liu, Shuohang Wang, Chenguang Zhu, Michael Zeng:
InheritSumm: A General, Versatile and Compact Summarizer by Distilling from GPT. CoRR abs/2305.13083 (2023) - [i10]Ruochen Xu, Song Wang, Yang Liu, Shuohang Wang, Yichong Xu, Dan Iter, Chenguang Zhu, Michael Zeng:
LMGQS: A Large-scale Dataset for Query-focused Summarization. CoRR abs/2305.13086 (2023) - [i9]Dan Iter, Reid Pryzant, Ruochen Xu, Shuohang Wang, Yang Liu, Yichong Xu, Chenguang Zhu:
In-Context Demonstration Selection with Cross Entropy Difference. CoRR abs/2305.14726 (2023) - [i8]Siru Ouyang, Shuohang Wang, Yang Liu, Ming Zhong, Yizhu Jiao, Dan Iter, Reid Pryzant, Chenguang Zhu, Heng Ji, Jiawei Han:
The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions. CoRR abs/2310.12418 (2023) - [i7]Zhihan Zhang, Shuohang Wang, Wenhao Yu, Yichong Xu, Dan Iter, Qingkai Zeng, Yang Liu, Chenguang Zhu, Meng Jiang:
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models. CoRR abs/2310.13127 (2023) - 2022
- [b1]Dan Iter:
Pre-finetuning methods for domain and task adaptation, with applications to discourse and translation. Stanford University, USA, 2022 - [c9]David Grangier, Dan Iter:
The Trade-offs of Domain Adaptation for Neural Language Models. ACL (1) 2022: 3802-3813 - [i6]Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang:
Generate rather than Retrieve: Large Language Models are Strong Context Generators. CoRR abs/2209.10063 (2022) - 2021
- [c8]William Held
, Dan Iter, Dan Jurafsky:
Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. EMNLP (1) 2021: 1406-1417 - [i5]Dan Iter, David Grangier:
On the Complementarity of Data Selection and Fine Tuning for Domain Adaptation. CoRR abs/2109.07591 (2021) - [i4]Dan Iter, David Grangier:
The Trade-offs of Domain Adaptation for Neural Language Models. CoRR abs/2109.10274 (2021) - [i3]William Held, Dan Iter, Dan Jurafsky:
Focus on what matters: Applying Discourse Coherence Theory to Cross Document Coreference. CoRR abs/2110.05362 (2021) - 2020
- [c7]Dan Iter, Kelvin Guu, Larry Lansing, Dan Jurafsky:
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. ACL 2020: 4859-4870 - [i2]Dan Iter, Kelvin Guu, Larry Lansing, Dan Jurafsky:
Pretraining with Contrastive Sentence Objectives Improves Discourse Performance of Language Models. CoRR abs/2005.10389 (2020)
2010 – 2019
- 2019
- [j1]Sadjad Fouladi, Francisco Romero, Dan Iter, Qian Li, Alex Ozdemir, Shuvo Chatterjee, Matei Zaharia, Christos Kozyrakis, Keith Winstein:
Outsourcing Everyday Jobs to Thousands of Cloud Functions with gg. login Usenix Mag. 44(3) (2019) - [c6]Sadjad Fouladi, Francisco Romero, Dan Iter, Qian Li, Shuvo Chatterjee, Christos Kozyrakis, Matei Zaharia, Keith Winstein:
From Laptop to Lambda: Outsourcing Everyday Jobs to Thousands of Transient Functional Containers. USENIX Annual Technical Conference 2019: 475-488 - 2018
- [c5]Dan Iter, Jong Yoon, Dan Jurafsky:
Automatic Detection of Incoherent Speech for Diagnosing Schizophrenia. CLPsych@NAACL-HTL 2018: 136-146 - [c4]Dan Iter, Alon Y. Halevy, Wang-Chiew Tan:
FrameIt: Ontology Discovery for Noisy User-Generated Text. NUT@EMNLP 2018: 173-183 - 2017
- [c3]Paroma Varma, Dan Iter, Christopher De Sa, Christopher Ré:
Flipper: A Systematic Approach to Debugging Training Sets. HILDA@SIGMOD 2017: 5:1-5:5 - 2016
- [i1]Rose Yu, Paroma Varma, Dan Iter, Christopher De Sa, Christopher Ré:
Socratic Learning. CoRR abs/1610.08123 (2016) - 2012
- [c2]Hila Becker, Dan Iter, Mor Naaman, Luis Gravano:
Identifying content for planned events across social media sites. WSDM 2012: 533-542 - 2011
- [c1]Hila Becker, Feiyang Chen, Dan Iter, Mor Naaman, Luis Gravano:
Automatic Identification and Presentation of Twitter Content for Planned Events. ICWSM 2011
Coauthor Index
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last updated on 2023-10-28 21:39 CEST by the dblp team
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