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Large Language Models (LLMs) have demonstrated impressive capabilities in creative tasks such as storytelling and E-mail generation.
Measuring nominal scale agreement among many raters
Joseph L Fleiss · 1971
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Learning string-edit distance
Eric Sven Ristad and Peter N Yianilos · 1998
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Latent dirichlet allocation
David M Blei, Andrew Y Ng, and Michael I Jordan · 2003
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Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard Hovy · 2003
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Learning word vectors for sentiment analysis
Andrew Maas, Raymond E Daly, Peter T Pham, Dan Huang, Andrew Y Ng, and Christopher Potts · 2011
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Paraphrasing for style
Wei Xu, Alan Ritter, William B Dolan, Ralph Grishman, and Colin Cherry · 2012
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A large annotated corpus for learning natural language inference
Samuel Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning · 2015
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Ground truth for grammatical error correction metrics
Courtney Napoles, Keisuke Sakaguchi, Matt Post, and Joel Tetreault · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun · 2015
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Optimizing statistical machine translation for text simplification
Wei Xu, Courtney Napoles, Ellie Pavlick, Quanze Chen, and Chris Callison-Burch · 2016
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Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec · 2017
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A discourse-aware attention model for abstractive summarization of long documents
Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian · 2018
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Dear sir or madam, may i introduce the gyafc dataset: Corpus, benchmarks and metrics for formality style transfer
Sudha Rao and Joel Tetreault · 2018
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Adafactor: Adaptive learning rates with sublinear memory cost
Noam Shazeer and Mitchell Stern · 2018
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Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
Alexander Richard Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir Radev · 2019
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Revisiting self-training for neural sequence generation
Junxian He, Jiatao Gu, Jiajun Shen, and Marc’Aurelio Ranzato · 2019
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Billsum: A corpus for automatic summarization of us legislation
Anastassia Kornilova and Vlad Eidelman · 2019
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Compressive transformers for long-range sequence modelling, 2019
Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, and Timothy P. Lillicrap · 2019
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Bigpatent: A large-scale dataset for abstractive and coherent summarization
Eva Sharma, Chen Li, and Lu Wang · 2019
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Style transfer for texts: Retrain, report errors, compare with rewrites
Alexey Tikhonov, Viacheslav Shibaev, Aleksander Nagaev, Aigul Nugmanova, and Ivan P Yamshchikov · 2019
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This email could save your life: Introducing the task of email subject line generation
Rui Zhang and Joel Tetreault · 2019
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ASSET: A dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations
Fernando Alva-Manchego, Louis Martin, Antoine Bordes, Carolina Scarton, Benoît Sagot, and Lucia Specia · 2020
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al · 2022
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Editeval: An instruction-based benchmark for text improvements
Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang, Maria Lomeli, Patrick Lewis, Gautier Izacard, Edouard Grave, Sebastian Riedel, and Fabio Petroni · 2022
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True: Re-evaluating factual consistency evaluation
Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, and Yossi Matias · 2022
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Large language models can self-improve
Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, and Jiawei Han · 2022
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Fruit: Faithfully reflecting updated information in text
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Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Felix Faltings, Michel Galley, Gerold Hintz, Chris Brockett, Chris Quirk, Jianfeng Gao, and Bill Dolan · 2020
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Wiki-40b: Multilingual language model dataset
Mandy Guo, Zihang Dai, Denny Vrandečić, and Rami Al-Rfou · 2020
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Automatically neutralizing subjective bias in text
Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, and Diyi Yang · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Textsettr: Few-shot text style extraction and tunable targeted restyling
Parker Riley, Noah Constant, Mandy Guo, Girish Kumar, David Uthus, and Zarana Parekh · 2020
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Unsupervised paraphrasing via deep reinforcement learning
AB Siddique, Samet Oymak, and Vagelis Hristidis · 2020
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Robert Iv, Alexandre Passos, Sameer Singh, and Ming-Wei Chang · 2022
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Edit5: Semi-autoregressive text-editing with t5 warm-start
Jonathan Mallinson, Jakub Adamek, Eric Malmi, and Aliaksei Severyn · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Improving wikipedia verifiability with ai
F Petroni, S Broscheit, A Piktus, P Lewis, G Izacard, L Hosseini, J Dwivedi-Yu, M Lomeli, T Schick, P Mazaré, et al · 2022
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Multitask prompted training enables zero-shot task generalization
Victor Sanh, Albert Webson, Colin Raffel, Stephen H Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, et al · 2022
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Peer: A collaborative language model
Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, and Sebastian Riedel · 2022
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, March 2023
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing · 2023
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Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung · 2023
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Palm 2 technical report
Alex Passos, Andrew Dai, Bryan Richter, Christopher Choquette, Daniel Sohn, David So, Dmitry (Dima) Lepikhin, Emanuel Taropa, Eric Ni, Erica Moreira, Gaurav Mishra, Jiahui Yu, Jon Clark, Kathy Meier-Hellstern, Kevin Robinson, Kiran Vodrahalli, Mark Omernick, Maxim Krikun, Maysam Moussalem, Melvin Johnson, Nan Du, Orhan Firat, Paige Bailey, Rohan Anil, Sebastian Ruder, Siamak Shakeri, Siyuan Qiao, Slav Petrov, Xavier Garcia, Yanping Huang, Yi Tay, Yong Cheng, Yonghui Wu, Yuanzhong Xu, Yujing Zhang, and Zack Nado · 2023
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Is chatgpt a general-purpose natural language processing task solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, and Diyi Yang · 2023
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Jfleg: A fluency corpus and benchmark for grammatical error correction
Courtney Napoles, Keisuke Sakaguchi, and Joel Tetreault · 2037
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