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In this technical report, we introduce Effidit (Efficient and Intelligent Editing), a digital writing assistant that facilitates users to write higher-quality text more efficiently by using artificial intelligence (AI) technologies.
Language models are few-shot learners
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Lcqmc: A large-scale chinese question matching corpus
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Measuring nominal scale agreement among many raters
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Conditional random fields: Probabilistic models for segmenting and labeling sequence data
John D. Lafferty, Andrew McCallum, and Fernando C. N. Pereira · 2001
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The probabilistic relevance framework: Bm25 and beyond
Stephen E. Robertson and Hugo Zaragoza · 2009
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Corpus-based semantic class mining: distributional vs. pattern-based approaches
Shuming Shi, Huibin Zhang, Xiaojie Yuan, and Ji-Rong Wen · 2010
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
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What is a paraphrase?
Rahul Bhagat and Eduard Hovy · 2013
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From word embeddings to document distances
Matt Kusner, Yu Sun, Nicholas Kolkin, and Kilian Weinberger · 2015
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A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and William B Dolan · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Paraphrasing revisited with neural machine translation
Jonathan Mallinson, Rico Sennrich, and Mirella Lapata · 2017
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Directional skip-gram: Explicitly distinguishing left and right context for word embeddings
Yan Song, Shuming Shi, Jing Li, and Haisong Zhang · 2018
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The bq corpus: A large-scale domain-specific chinese corpus for sentence semantic equivalence identification
Jing Chen, Qingcai Chen, Xin Liu, Haijun Yang, Daohe Lu, and Buzhou Tang · 2018
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How contextual are contextualized word representations? comparing the geometry of bert, elmo, and GPT-2 embeddings
Kawin Ethayarajh · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Cited alongside, same era.
Transformer-xl: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, and Ruslan Salakhutdinov · 2019
Cited alongside, same era.
Faspell: A fast, adaptable, simple, powerful chinese spell checker based on dae-decoder paradigm
Yuzhong Hong, Xianguo Yu, Neng He, Nan Liu, and Junhui Liu · 2019
Cited alongside, same era.
Multilingual whispers: Generating paraphrases with translation
Christian Federmann, Oussama Elachqar, and Chris Quirk · 2019
Cited alongside, same era.
Billion-scale similarity search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Texsmart: A text understanding system for fine-grained ner and enhanced semantic analysis
Haisong Zhang, Lemao Liu, Haiyun Jiang, Yangming Li, Enbo Zhao, Kun Xu, Linfeng Song, Suncong Zheng, Botong Zhou, Jianchen Zhu, Xiao Feng, Tao Chen, Tao Yang, Dong Yu, Feng Zhang, Zhanhui Kang, and Shuming Shi · 2020
Later among the works it cites.
Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer · 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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Enabling language models to fill in the blanks
Chris Donahue, Mina Lee, and Percy Liang · 2020
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Attention is not all you need: pure attention loses rank doubly exponentially with depth
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Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova · 2019
Cited alongside, same era.
The second conversational intelligence challenge (convai2)
Emily Dinan, Varvara Logacheva, Valentin Malykh, Alexander Miller, Kurt Shuster, Jack Urbanek, Douwe Kiela, Arthur Szlam, Iulian Serban, Ryan Lowe, et al · 2020
Cited alongside, same era.
Neural text generation with unlikelihood training
Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, and Jason Weston · 2020
Cited alongside, same era.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush · 2020
Cited alongside, same era.
Generalization through memorization: Nearest neighbor language models
Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis · 2020
Cited alongside, same era.
GECToR – grammatical error correction: Tag, not rewrite
Kostiantyn Omelianchuk, Vitaliy Atrasevych, Artem Chernodub, and Oleksandr Skurzhanskyi · 2020
Cited alongside, same era.
Yihe Dong, Jean-Baptiste Cordonnier, and Andreas Loukas · 2021
Later among the works it cites.
Adaptive semiparametric language models
Dani Yogatama, Cyprien de Masson d’Autume, and Lingpeng Kong · 2021
Later among the works it cites.
Tail-to-tail non-autoregressive sequence prediction for chinese grammatical error correction
Piji Li and Shuming Shi · 2021
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PLOME: Pre-training with misspelled knowledge for Chinese spelling correction
Shulin Liu, Tao Yang, Tianchi Yue, Feng Zhang, and Di Wang · 2021
Later among the works it cites.
Keep the primary, rewrite the secondary: A two-stage approach for paraphrase generation
Yixuan Su, David Vandyke, Simon Baker, Yan Wang, and Nigel Collier · 2021
Later among the works it cites.
SimCSE: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen · 2021
Later among the works it cites.
TaCL: Improving BERT pre-training with token-aware contrastive learning
Yixuan Su, Fangyu Liu, Zaiqiao Meng, Tian Lan, Lei Shu, Ehsan Shareghi, and Nigel Collier · 2022
Closest in time.
A contrastive framework for neural text generation
Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong, and Nigel Collier · 2022
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Language models can see: Plugging visual controls in text generation
Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu, Dani Yogatama, Yan Wang, Lingpeng Kong, and Nigel Collier · 2022
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Pretraining chinese bert for detecting word insertion and deletion errors, 2022
Cong Zhou, Yong Dai, Duyu Tang, Enbo Zhao, Zhangyin Feng, Li Kuang, and Shuming Shi · 2022
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