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Generative Large Language Models (LLMs) have become the mainstream choice for fewshot and zeroshot learning thanks to the universality of text generation.
Adversarial NLI: A New Benchmark for Natural Language Understanding
Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, and Douwe Kiela. 2020 · 1910
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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 · 1910
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ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2003
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Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales
Bo Pang and Lillian Lee. 2005 · 2005
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The PASCAL Recognising Textual Entailment Challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2006 · 2006
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It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners
Timo Schick and Hinrich Schütze. 2021b · 2009
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Wenpeng Yin, Nazneen Fatema Rajani, Dragomir Radev, Richard Socher, and Caiming Xiong. 2020 · 2010
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Contributions to the study of SMS spam filtering: new collection and results
Tiago A. Almeida, José María G. Hidalgo, and Akebo Yamakami. 2011 · 2011
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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
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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
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Hidden factors and hidden topics: understanding rating dimensions with review text
Julian McAuley and Jure Leskovec. 2013 · 2013
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Good debt or bad debt: Detecting semantic orientations in economic texts
Pekka Malo, Ankur Sinha, Pekka Korhonen, Jyrki Wallenius, and Pyry Takala. 2014 · 2014
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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US State of the Union Speeches
Policy Agendas Project. 2015 · 2015
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Yelp Dataset Challenge is Doubling Up!
R Soups. 2015 · 2015
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Character-level Convolutional Networks for Text Classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Toxic Comment Classification Challenge
C.J Adams, Will Cukierski, Jeffrey Sorensen, Julia Elliott, Lucas Dixon, Mark McDonald, and nithum. 2017 · 2017
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Automated Hate Speech Detection and the Problem of Offensive Language
Thomas Davidson, Dana Warmsley, Michael Macy, and Ingmar Weber. 2017 · 2017
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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
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XNLI: Evaluating Cross-lingual Sentence Representations
Alexis Conneau, Guillaume Lample, Ruty Rinott, Adina Williams, Samuel R. Bowman, Holger Schwenk, and Veselin Stoyanov. 2018 · 2018
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Identifying Well-formed Natural Language Questions
Manaal Faruqui and Dipanjan Das. 2018 · 2018
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CARER: Contextualized Affect Representations for Emotion Recognition
Elvis Saravia, Hsien-Chi Toby Liu, Yen-Hao Huang, Junlin Wu, and Yi-Shin Chen. 2018 · 2018
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FEVER: a large-scale dataset for Fact Extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018 · 2018
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A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
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SemEval-2019 Task 3: EmoContext Contextual Emotion Detection in Text
Ankush Chatterjee, Kedhar Nath Narahari, Meghana Joshi, and Puneet Agrawal. 2019 · 2019
Cited alongside, same era.
Language Models are Unsupervised Multitask Learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Training Compute-Optimal Large Language Models
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katie Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Jack W. Rae, Oriol Vinyals, and Laurent Sifre. 2022 · 2022
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WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation
Alisa Liu, Swabha Swayamdipta, Noah A. Smith, and Yejin Choi. 2022 · 2022
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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, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
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Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
Ofir Press, Noah A. Smith, and Mike Lewis. 2022 · 2022
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Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset
Hannah Rashkin, Eric Michael Smith, Margaret Li, and Y-Lan Boureau. 2019 · 2019
Cited alongside, same era.
Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
Wenpeng Yin, Jamaal Hay, and Dan Roth. 2019 · 2019
Cited alongside, same era.
Manifesto Corpus
Tobias Burst, Krause Werner, Pola Lehmann, Lewandowski Jirka, Theres Mattheiß, Nicolas Merz, Sven Regel, and Lisa Zehnter. 2020 · 2020
Cited alongside, same era.
Efficient Intent Detection with Dual Sentence Encoders
Iñigo Casanueva, Tadas Temčinas, Daniela Gerz, Matthew Henderson, and Ivan Vulić. 2020 · 2020
Cited alongside, same era.
Social Bias Frames: Reasoning about Social and Power Implications of Language
Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A. Smith, and Yejin Choi. 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.
FLEX: Unifying Evaluation for Few-Shot NLP
Jonathan Bragg, Arman Cohan, Kyle Lo, and Iz Beltagy. 2021 · 2021
Cited alongside, same era.
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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, Manan Dey, M. Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Fevry, Jason Alan Fries, Ryan Teehan, Tali Bers, Stella Biderman, Leo Gao, Thomas Wolf, and Alexander M. Rush. 2022 · 2022
Later among the works it cites.
Yi Sun, Yu Zheng, Chao Hao, and Hangping Qiu. 2022 · 2022
Later among the works it cites.
Prompting ELECTRA: Few-Shot Learning with Discriminative Pre-Trained Models
Mengzhou Xia, Mikel Artetxe, Jingfei Du, Danqi Chen, and Veselin Stoyanov. 2022 · 2022
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Prompt Tuning for Discriminative Pre-trained Language Models
Yuan Yao, Bowen Dong, Ao Zhang, Zhengyan Zhang, Ruobing Xie, Zhiyuan Liu, Leyu Lin, Maosong Sun, and Jianyong Wang. 2022 · 2022
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GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
Joshua Ainslie, James Lee-Thorp, Michiel de Jong, Yury Zemlyanskiy, Federico Lebrón, and Sumit Sanghai. 2023 · 2023
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MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages
Jack FitzGerald, Christopher Hench, Charith Peris, Scott Mackie, Kay Rottmann, Ana Sanchez, Aaron Nash, Liam Urbach, Vishesh Kakarala, Richa Singh, Swetha Ranganath, Laurie Crist, Misha Britan, Wouter Leeuwis, Gokhan Tur, and Prem Natarajan. 2023 · 2023
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TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models
Zorik Gekhman, Jonathan Herzig, Roee Aharoni, Chen Elkind, and Idan Szpektor. 2023 · 2023
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OpenAI. 2023 · 2023
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Model-tuning Via Prompts Makes NLP Models Adversarially Robust
Mrigank Raman, Pratyush Maini, J. Zico Kolter, Zachary C. Lipton, and Danish Pruthi. 2023 · 2023
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tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
Damien Sileo. 2023 · 2023
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RoFormer: Enhanced Transformer with Rotary Position Embedding
Jianlin Su, Yu Lu, Shengfeng Pan, Ahmed Murtadha, Bo Wen, and Yunfeng Liu. 2023 · 2023
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Alpaca: A Strong, Replicable Instruction-Following Model
Rohan Taori, Ishaan Gulrajani, Zhang Tianyi, Yann Dubois, Li Xuechen, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
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Llama 2: Open Foundation and Fine-Tuned Chat Models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023 · 2023
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Zephyr: Direct Distillation of LM Alignment
Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, and Thomas Wolf. 2023 · 2023
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A Universal Discriminator for Zero-Shot Generalization
Haike Xu, Zongyu Lin, Jing Zhou, Yanan Zheng, and Zhilin Yang. 2023 · 2023
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LIMA: Less Is More for Alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, and Omer Levy. 2023 · 2023
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yahoo_answers_topics · Datasets at Hugging Face
Unknown. 2024 · 2024
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