Fetching the paper…
Reading the bibliography…
Few-shot text classification systems have impressive capabilities but are infeasible to deploy and use reliably due to their dependence on prompting and billion-parameter language models.
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.
Twenty Newsgroups
Tom Mitchell. 1999 · 1999
Earlier work this paper cites.
Introduction to Information Retrieval
Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schütze. 2008 · 2008
Earlier work this paper cites.
The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson and Hugo Zaragoza. 2009 · 2009
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.
API design for machine learning software: experiences from the scikit-learn project
Lars Buitinck, Gilles Louppe, Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler, Robert Layton, Jake VanderPlas, Arnaud Joly, Brian Holt, and Gaël Varoquaux. 2013 · 2013
Earlier work this paper cites.
Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, and Christopher Potts. 2013 · 2013
Earlier work this paper cites.
Siamese neural networks for one-shot image recognition
Gregory Koch, Richard Zemel, Ruslan Salakhutdinov, et al. 2015 · 2015
Earlier work this paper cites.
Automated hate speech detection and the problem of offensive language
Thomas Davidson, Dana Warmsley, Michael Macy, and Ingmar Weber. 2017 · 2017
Earlier work this paper cites.
Content Moderation , pages 1–4. Springer International Publishing, Cham
Sarah T. Roberts. 2017 · 2017
Earlier work this paper cites.
Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
“Liar, liar pants on fire”: A new benchmark dataset for fake news detection
William Yang Wang. 2017 · 2017
Earlier work this paper cites.
Evaluation of sentence embeddings in downstream and linguistic probing tasks
Christian S. Perone, Roberto Pereira Silveira, and Thomas S. Paula. 2018 · 2018
Cited alongside, same era.
The spread of true and false news online
Soroush Vosoughi, Deb Roy, and Sinan Aral. 2018 · 2018
Cited alongside, same era.
SemEval-2019 task 5: Multilingual detection of hate speech against immigrants and women in Twitter
Valerio Basile, Cristina Bosco, Elisabetta Fersini, Debora Nozza, Viviana Patti, Francisco Manuel Rangel Pardo, Paolo Rosso, and Manuela Sanguinetti. 2019 · 2019
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 · 2019
Cited alongside, same era.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
It’s not just size that matters: Small language models are also few-shot learners
Timo Schick and Hinrich Schütze. 2021b · 2021
Later among the works it cites.
Improving and simplifying pattern exploiting training
Derek Tam, Rakesh R. Menon, Mohit Bansal, Shashank Srivastava, and Colin Raffel. 2021 · 2021
Later among the works it cites.
Human parity on commonsenseqa: Augmenting self-attention with external attention
Yichong Xu, Chenguang Zhu, Shuohang Wang, Siqi Sun, Hao Cheng, Xiaodong Liu, Jianfeng Gao, Pengcheng He, Michael Zeng, and Xuedong Huang. 2021 · 2021
Later among the works it cites.
CML: A contrastive meta learning method to estimate human label confidence scores and reduce data collection cost
Bo Dong, Yiyi Wang, Hanbo Sun, Yunji Wang, Alireza Hashemi, and Zheng Du. 2022 · 2022
Later among the works it cites.
The psychological drivers of misinformation belief and its resistance to correction
Ullrich K. H. Ecker, Stephan Lewandowsky, John Cook, Philipp Schmid, Lisa K. Fazio, Nadia Brashier, Panayiota Kendeou, Emily K. Vraga, and Michelle A. Amazeen. 2022 · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Superglue: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 2019 · 2019
Cited alongside, same era.
GoEmotions: A dataset of fine-grained emotions
Dorottya Demszky, Dana Movshovitz-Attias, Jeongwoo Ko, Alan Cowen, Gaurav Nemade, and Sujith Ravi. 2020 · 2020
Cited alongside, same era.
The multilingual amazon reviews corpus
Phillip Keung, Yichao Lu, György Szarvas, and Noah A. Smith. 2020 · 2020
Cited alongside, same era.
Mpnet: Masked and permuted pre-training for language understanding
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu. 2020 · 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 · 2020
Cited alongside, same era.
RAFT: A real-world few-shot text classification benchmark
Neel Alex, Eli Lifland, Lewis Tunstall, Abhishek Thakur, Pegah Maham, C. Jess Riedel, Emmie Hine, Carolyn Ashurst, Paul Sedille, Alexis Carlier, Michael Noetel, and Andreas Stuhlmüller. 2021 · 2021
Cited alongside, same era.
I wish I would have loved this one, but I didn’t – a multilingual dataset for counterfactual detection in product review
James O’Neill, Polina Rozenshtein, Ryuichi Kiryo, Motoko Kubota, and Danushka Bollegala. 2021 · 2021
Cited alongside, same era.
Later among the works it cites.
Prompt-free and efficient few-shot learning with language models
Rabeeh Karimi Mahabadi, Luke Zettlemoyer, James Henderson, Lambert Mathias, Marzieh Saeidi, Veselin Stoyanov, and Majid Yazdani. 2022 · 2022
Later among the works it cites.
What makes good in-context examples for GPT-3?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, and Weizhu Chen. 2022b · 2022
Later among the works it cites.
A holistic approach to undesired content detection
Todor Markov, Chong Zhang, Sandhini Agarwal, Tyna Eloundou, Teddy Lee, Steven Adler, Angela Jiang, and Lilian Weng. 2022 · 2022
Later among the works it cites.
True few-shot learning with Prompts—A real-world perspective
Timo Schick and Hinrich Schütze. 2022 · 2022
Later among the works it cites.
Textual content moderation in C2C marketplace
Yusuke Shido, Hsien-Chi Liu, and Keisuke Umezawa. 2022 · 2022
Later among the works it cites.
Efficient few-shot learning without prompts
Lewis Tunstall, Nils Reimers, Unso Eun Seo Jo, Luke Bates, Daniel Korat, Moshe Wasserblat, and Oren Pereg. 2022 · 2022
Later among the works it cites.
Training data is more valuable than you think: A simple and effective method by retrieving from training data
Shuohang Wang, Yichong Xu, Yuwei Fang, Yang Liu, Siqi Sun, Ruochen Xu, Chenguang Zhu, and Michael Zeng. 2022 · 2022
Later among the works it cites.
Multilingual content moderation: A case study on reddit
Meng Ye, Karan Sikka, Katherine Atwell, Sabit Hassan, Ajay Divakaran, and Malihe Alikhani. 2023 · 2023
Closest in time.