Fetching the paper…
Reading the bibliography…
Style representation learning builds content-independent representations of author style in text.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
Earlier work this paper cites.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
Earlier work this paper cites.
Inference in an authorship problem
Frederick Mosteller and David L. Wallace. 1963 · 1963
Earlier work this paper cites.
Authorship attribution
David I. Holmes. 1994 · 1994
Earlier work this paper cites.
Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, T. J. Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeff Wu, and Dario Amodei. 2020 · 2001
Earlier work this paper cites.
The linguist on the witness stand: Forensic linguistics in american courts
Peter Tiersma and Lawrence M. Solan. 2002 · 2002
Earlier work this paper cites.
The importance of suppressing domain style in authorship analysis
Sebastian Bischoff, Niklas Deckers, Marcel Schliebs, Ben Thies, Matthias Hagen, Efstathios Stamatatos, Benno Stein, and Martin Potthast. 2020 · 2005
Earlier work this paper cites.
Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
Bo Pang and Lillian Lee. 2005 · 2005
Earlier work this paper cites.
Computational methods in authorship attribution
Moshe Koppel, Jonathan Schler, and Shlomo Argamon. 2009 · 2009
Earlier work this paper cites.
A survey of modern authorship attribution methods
Efstathios Stamatatos. 2009 · 2009
Earlier work this paper cites.
The psychological meaning of words: Liwc and computerized text analysis methods
Yla R Tausczik and James W Pennebaker. 2010 · 2010
Earlier work this paper cites.
Simple English Wikipedia: A new text simplification task
William Coster and David Kauchak. 2011 · 2011
Earlier work this paper cites.
Learning word vectors for sentiment analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011 · 2011
Earlier work this paper cites.
TSATC: Twitter Sentiment Analysis Training Corpus
Ibrahim Naji. 2012 · 2012
Earlier work this paper cites.
Do deep nets really need to be deep?
Jimmy Ba and Rich Caruana. 2014 · 2014
Earlier work this paper cites.
SimLex-999: Evaluating semantic models with (genuine) similarity estimation
Felix Hill, Roi Reichart, and Anna Korhonen. 2015 · 2015
Earlier work this paper cites.
Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin. 2015 · 2015
Earlier work this paper cites.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
Earlier work this paper cites.
An empirical analysis of formality in online communication
Ellie Pavlick and Joel Tetreault. 2016 · 2016
Earlier work this paper cites.
Overview of pan’16: new challenges for authorship analysis: cross-genre profiling, clustering, diarization, and obfuscation
Paolo Rosso, Francisco Rangel, Martin Potthast, Efstathios Stamatatos, Michael Tschuggnall, and Benno Stein. 2016 · 2016
Earlier work this paper cites.
Android apps and user feedback: A dataset for software evolution and quality improvement
Giovanni Grano, Andrea Di Sorbo, Francesco Mercaldo, Corrado A. Visaggio, Gerardo Canfora, and Sebastiano Panichella. 2017 · 2017
Earlier work this paper cites.
A study of style in machine translation: Controlling the formality of machine translation output
Xing Niu, Marianna Martindale, and Marine Carpuat. 2017 · 2017
Cited alongside, same era.
Personalized machine translation: Preserving original author traits
Ella Rabinovich, Raj Nath Patel, Shachar Mirkin, Lucia Specia, and Shuly Wintner. 2017 · 2017
Cited alongside, same era.
Style transfer from non-parallel text by cross-alignment
Tianxiao Shen, Tao Lei, Regina Barzilay, and Tommi Jaakkola. 2017 · 2017
Cited alongside, same era.
From shakespeare to Twitter: What are language styles all about?
Wei Xu. 2017 · 2017
Cited alongside, same era.
Hate Speech Dataset from a White Supremacy Forum
Ona de Gibert, Naiara Perez, Aitor García-Pablos, and Montse Cuadros. 2018 · 2018
Cited alongside, same era.
Style transfer in text: Exploration and evaluation
Zhenxin Fu, Xiaoye Tan, Nanyun Peng, Dongyan Zhao, and Rui Yan. 2018 · 2018
Supervised contrastive learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan. 2020 · 2020
Later among the works it cites.
Automatically neutralizing subjective bias in text
Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, and Diyi Yang. 2020 · 2020
Later among the works it 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. 2020 · 2020
Later among the works it cites.
BLiMP: The benchmark of linguistic minimal pairs for English
Alex Warstadt, Alicia Parrish, Haokun Liu, Anhad Mohananey, Wei Peng, Sheng-Fu Wang, and Samuel R. Bowman. 2020 · 2020
Later among the works it cites.
A deep metric learning approach to account linking
Aleem Khan, Elizabeth Fleming, Noah Schofield, Marcus Bishop, and Nicholas Andrews. 2021 · 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…
Cited alongside, same era.
Style transfer through back-translation
Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, and Alan W Black. 2018 · 2018
Cited alongside, same era.
Dear sir or madam, may I introduce the GYAFC dataset: Corpus, benchmarks and metrics for formality style transfer
Sudha Rao and Joel Tetreault. 2018 · 2018
Cited alongside, same era.
CARER: Contextualized affect representations for emotion recognition
Elvis Saravia, Hsien-Chi Toby Liu, Yen-Hao Huang, Junlin Wu, and Yi-Shin Chen. 2018 · 2018
Cited alongside, same era.
Learning invariant representations of social media users
Nicholas Andrews and Marcus Bishop. 2019 · 2019
Cited alongside, same era.
Similarity learning for authorship verification in social media
Benedikt Boenninghoff, Robert M Nickel, Steffen Zeiler, and Dorothea Kolossa. 2019 · 2019
Cited alongside, same era.
Style transformer: Unpaired text style transfer without disentangled latent representation
Ning Dai, Jianze Liang, Xipeng Qiu, and Xuan-Jing Huang. 2019 · 2019
Cited alongside, same era.
Frederick Liu, Siamak Shakeri, Hongkun Yu, and Jing Li. 2021 · 2021
Later among the works it cites.
Textsettr: Few-shot text style extraction and tunable targeted restyling
Parker Riley, Noah Constant, Mandy Guo, Girish Kumar, David C Uthus, and Zarana Parekh. 2021 · 2021
Later among the works it cites.
Learning universal authorship representations
Rafael A Rivera-Soto, Olivia Elizabeth Miano, Juanita Ordonez, Barry Y Chen, Aleem Khan, Marcus Bishop, and Nicholas Andrews. 2021 · 2021
Later among the works it cites.
Does it capture stel? a modular, similarity-based linguistic style evaluation framework
Anna Wegmann and Dong Nguyen. 2021 · 2021
Later among the works it cites.
Text style transfer via learning style instance supported latent space
Xiaoyuan Yi, Zhenghao Liu, Wenhao Li, and Maosong Sun. 2021 · 2021
Later among the works it cites.
Idiosyncratic but not arbitrary: Learning idiolects in online registers reveals distinctive yet consistent individual styles
Jian Zhu and David Jurgens. 2021 · 2021
Later among the works it cites.
APPDIA: A discourse-aware transformer-based style transfer model for offensive social media conversations
Katherine Atwell, Sabit Hassan, and Malihe Alikhani. 2022 · 2022
Later among the works it cites.
Unnatural instructions: Tuning language models with (almost) no human labor
Or Honovich, Thomas Scialom, Omer Levy, and Timo Schick. 2022 · 2022
Later among the works it cites.
Large language models can self-improve
Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, and Jiawei Han. 2022 · 2022
Later among the works it cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Later among the works it cites.
Low-resource authorship style transfer with in-context learning
Ajay Patel, Nicholas Andrews, and Chris Callison-Burch. 2022 · 2022
Later among the works it cites.
Self-instruct: Aligning language model with self generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2022 · 2022
Later among the works it cites.
Same author or just same topic? towards content-independent style representations
Anna Wegmann, Marijn Schraagen, Dong Nguyen, et al. 2022 · 2022
Later among the works it cites.
Kangchen Zhu, Zhiliang Tian, Ruifeng Luo, and Xiaoguang Mao. 2022 · 2022
Later among the works it cites.
Amazon Customer Reviews Dataset — s3.amazonaws.com
Inc. Amazon.com. 2018 · 2023
Closest in time.
Twitter User Gender Classification — kaggle.com
CrowdFlower. 2017 · 2023
Closest in time.
Chatgpt outperforms crowd-workers for text-annotation tasks
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli. 2023 · 2023
Closest in time.