Fetching the paper…
Reading the bibliography…
The growing prominence of large language models, such as GPT-4 and ChatGPT, has led to increased concerns over academic integrity due to the potential for machine-generated content and paraphrasing.
Paws: Paraphrase adversaries from word scrambling, 2019
Yuan Zhang, Jason Baldridge, and Luheng He · 1904
Earlier work this paper cites.
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 · 1910
Earlier work this paper cites.
Support vector machines for paraphrase identification and corpus construction
Chris Brockett and Bill Dolan · 2005
Earlier work this paper cites.
Automatically constructing a corpus of sentential paraphrases
William B. Dolan and Chris Brockett · 2005
Earlier work this paper cites.
N-gram similarity and distance
Grzegorz Kondrak · 2005
Earlier work this paper cites.
Using syntactic information to identify plagiarism
Özlem Uzuner, Boris Katz, and Thade Nahnsen · 2005
Earlier work this paper cites.
A semantic similarity approach to paraphrase detection
Samuel Fernando and Mark Stevenson · 2009
Earlier work this paper cites.
Semantic similarity of short texts
Aminul Islam and Diana Inkpen · 2009
Earlier work this paper cites.
The gini index and measures of inequality
Frank A. Farris · 2010
Earlier work this paper cites.
Improving text simplification language modeling using unsimplified text data
David Kauchak · 2013
Earlier work this paper cites.
Efficient estimation of word representations in vector space, 2013
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
Earlier work this paper cites.
Microsoft coco: Common objects in context, 2014
Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Dollár · 2014
Earlier work this paper cites.
GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning · 2014
Earlier work this paper cites.
Improving statistical machine translation with a multilingual paraphrase database
Ramtin Mehdizadeh Seraj, Maryam Siahbani, and Anoop Sarkar · 2015
Earlier work this paper cites.
Enriching word vectors with subword information, 2016
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov · 2016
Earlier work this paper cites.
Czeng 1.6: Enlarged czech-english parallel corpus with processing tools dockered
Ondrej Bojar, Ondrej Dusek, Tom Kocmi, Jindřich Libovický, Michal Novák, Martin Popel, Roman Sudarikov, and Dusan Varis · 2016
Earlier work this paper cites.
A method for fuzzy string matching
Wen-Yen Wu · 2016
Earlier work this paper cites.
Learning to paraphrase for question answering
Li Dong, Jonathan Mallinson, Siva Reddy, and Mirella Lapata · 2017
Cited alongside, same era.
A continuously growing dataset of sentential paraphrases
Wuwei Lan, Siyu Qiu, Hua He, and Wei Xu · 2017
Cited alongside, same era.
Attention is all you need, 2017
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Bilateral multi-perspective matching for natural language sentences
Zhiguo Wang, Wael Hamza, and Radu Florian · 2017
Cited alongside, same era.
Plagiarism: Taxonomy, tools and detection techniques
Hussain A Chowdhury and Dhruba K Bhattacharyya · 2018
Cited alongside, same era.
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, Peter J Liu, et al · 2020
Later among the works it cites.
Enhanced word embeddings using multi-semantic representation through lexical chains
Terry Ruas, Charles P. H. Ferreira, William Gorsky, Fabrício O. França, and Débora M. R. Medeiros · 2020
Later among the works it cites.
Automatic machine translation evaluation in many languages via zero-shot paraphrasing
Brian Thompson and Matt Post · 2020
Later among the works it cites.
Small but mighty: New benchmarks for split and rephrase
Li Zhang, Huaiyu Zhu, Siddhartha Brahma, and Yunyao Li · 2020
Later among the works it cites.
Parasci: A large scientific paraphrase dataset for longer paraphrase generation, 2021
Qingxiu Dong, Xiaojun Wan, and Yue Cao · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
ETPC - a paraphrase identification corpus annotated with extended paraphrase typology and negation
Venelin Kovatchev, M. Antònia Martí, and Maria Salamó · 2018
Cited alongside, same era.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman · 2018
Cited alongside, same era.
ParaNMT-50M: Pushing the limits of paraphrastic sentence embeddings with millions of machine translations
John Wieting and Kevin Gimpel · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
Academic Plagiarism Detection: A Systematic Literature Review
Tomáš Foltýnek, Norman Meuschke, and Bela Gipp · 2019
Cited alongside, same era.
A qualitative evaluation framework for paraphrase identification
Venelin Kovatchev, M. Antonia Marti, Maria Salamo, and Javier Beltran · 2019
Cited alongside, same era.
Controllable Text Simplification with Explicit Paraphrasing
Mounica Maddela, Fernando Alva-Manchego, and Wei Xu · 2021
Later among the works it cites.
ConRPG: Paraphrase Generation using Contexts as Regularizer
Yuxian Meng, Xiang Ao, Qing He, Xiaofei Sun, Qinghong Han, Fei Wu, Chun Fan, and Jiwei Li · 2021
Later among the works it cites.
Improving paraphrase detection with the adversarial paraphrasing task
Animesh Nighojkar and John Licato · 2021
Later among the works it cites.
Are neural language models good plagiarists? a benchmark for neural paraphrase detection
Jan Philip Wahle, Terry Ruas, Norman Meuschke, and Bela Gipp · 2021
Later among the works it cites.
Aspect sentiment quad prediction as paraphrase generation
Wenxuan Zhang, Yang Deng, Xin Li, Yifei Yuan, Lidong Bing, and Wai Lam · 2021
Later among the works it cites.
Using paraphrases to study properties of contextual embeddings
Laura Burdick, Jonathan K. Kummerfeld, and Rada Mihalcea · 2022
Later among the works it cites.
Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text
Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, Noah Smith, and Yejin Choi · 2022
Later among the works it cites.
Analyzing multi-task learning for abstractive text summarization
Frederic Thomas Kirstein, Jan Philip Wahle, Terry Ruas, and Bela Gipp · 2022
Later among the works it cites.
How large language models are transforming machine-paraphrase plagiarism
Jan Philip Wahle, Terry Ruas, Frederic Kirstein, and Bela Gipp · 2022
Later among the works it cites.
GCPG: A General Framework for Controllable Paraphrase Generation
Kexin Yang, Dayiheng Liu, Wenqiang Lei, Baosong Yang, Haibo Zhang, Xue Zhao, Wenqing Yao, and Boxing Chen · 2022
Later among the works it cites.
OpenAI · 2023
Closest in time.
Ai usage cards: Responsibly reporting ai-generated content
Jan Philip Wahle, Terry Ruas, Saif M Mohammad, Norman Meuschke, and Bela Gipp · 2023
Closest in time.