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Prompt tuning (PT) which only tunes the embeddings of an additional sequence of tokens per task, keeping the pre-trained language model (PLM) frozen, has shown remarkable performance in few-shot learning.
Generalized inner loop meta-learning
Edward Grefenstette, Brandon Amos, Denis Yarats, Phu Mon Htut, Artem Molchanov, Franziska Meier, Douwe Kiela, Kyunghyun Cho, and Soumith Chintala. 2019 · 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. 2019 · 1910
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CrowS-pairs: A challenge dataset for measuring social biases in masked language models
Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel R. Bowman. 2020 · 1967
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Acquiring a single new word
Susan Carey and E. Bartlett. 1978 · 1978
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Evolutionary principles in self-referential learning. on learning now to learn: The meta-meta-meta…-hook
Jurgen Schmidhuber. 1987 · 1987
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Toward semantics-based answer pinpointing
Eduard Hovy, Laurie Gerber, Ulf Hermjakob, Chin-Yew Lin, and Deepak Ravichandran. 2001 · 2001
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Learning question classifiers
Xin Li and Dan Roth. 2002 · 2002
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 2005
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2005 · 2005
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Automatically constructing a corpus of sentential paraphrases
William B. Dolan and Chris Brockett. 2005 · 2005
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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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Ethos: an online hate speech detection dataset
Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos, and Grigorios Tsoumakas. 2020 · 2006
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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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Robust disambiguation of named entities in text
Johannes Hoffart, Mohamed Amir Yosef, Ilaria Bordino, Hagen Fürstenau, Manfred Pinkal, Marc Spaniol, Bilyana Taneva, Stefan Thater, and Gerhard Weikum. 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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Climate-fever: A dataset for verification of real-world climate claims
T. Diggelmann, Jordan L. Boyd-Graber, Jannis Bulian, Massimiliano Ciaramita, and Markus Leippold. 2020 · 2012
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SemEval-2012 task 7: Choice of plausible alternatives: An evaluation of commonsense causal reasoning
Andrew Gordon, Zornitsa Kozareva, and Melissa Roemmele. 2012 · 2012
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Development of a benchmark corpus to support the automatic extraction of drug-related adverse effects from medical case reports
Harsha Gurulingappa, Abdul Mateen Rajput, Angus Roberts, Juliane Fluck, Martin Hofmann-Apitius, and Luca Toldo. 2012 · 2012
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The winograd schema challenge
Hector J. Levesque, Ernest Davis, and Leora Morgenstern. 2012 · 2012
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Hatexplain: A benchmark dataset for explainable hate speech detection
Binny Mathew, Punyajoy Saha, Seid Muhie Yimam, Chris Biemann, Pawan Goyal, and Animesh Mukherjee. 2020 · 2012
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Annotated Gigaword
Courtney Napoles, Matthew Gormley, and Benjamin Van Durme. 2012 · 2012
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English-asl gloss parallel corpus 2012: Aslg-pc12
A. Othman and M. Jemni. 2012 · 2012
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Semantic parsing on Freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013 · 2013
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Hidden factors and hidden topics: understanding rating dimensions with review text
Julian J. McAuley and Jure Leskovec. 2013 · 2013
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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
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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 SICK cure for the evaluation of compositional distributional semantic models
Marco Marelli, Stefano Menini, Marco Baroni, Luisa Bentivogli, Raffaella Bernardi, and Roberto Zamparelli. 2014 · 2014
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Question-answer driven semantic role labeling: Using natural language to annotate natural language
Luheng He, Mike Lewis, and Luke Zettlemoyer. 2015 · 2015
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Siamese neural networks for one-shot image recognition
Gregory Koch, Richard Zemel, Ruslan Salakhutdinov, et al. 2015 · 2015
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Dbpedia - a large-scale, multilingual knowledge base extracted from wikipedia
Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, D. Kontokostas, Pablo N. Mendes, Sebastian Hellmann, M. Morsey, Patrick van Kleef, S. Auer, and C. Bizer. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Jake Zhao, and Yann LeCun. 2015 · 2015
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Neural text generation from structured data with application to the biography domain
Rémi Lebret, David Grangier, and Michael Auli. 2016 · 2016
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Meta-learning with memory-augmented neural networks
Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, and Timothy Lillicrap. 2016 · 2016
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, koray kavukcuoglu, and Daan Wierstra. 2016 · 2016
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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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Searchqa: A new q&a dataset augmented with context from a search engine
Matthew Dunn, Levent Sagun, Mike Higgins, V. U. Güney, Volkan Cirik, and Kyunghyun Cho. 2017 · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017 · 2017
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RACE: Large-scale ReAding comprehension dataset from examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy. 2017 · 2017
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Building machines that learn and think like people
Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, and Samuel J. Gershman. 2017 · 2017
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Zero-shot relation extraction via reading comprehension
Omer Levy, Minjoon Seo, Eunsol Choi, and Luke Zettlemoyer. 2017 · 2017
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Program induction by rationale generation: Learning to solve and explain algebraic word problems
Wang Ling, Dani Yogatama, Chris Dyer, and Phil Blunsom. 2017 · 2017
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel. 2017 · 2017
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Few-shot learning through an information retrieval lens
Eleni Triantafillou, Richard S. Zemel, and Raquel Urtasun. 2017 · 2017
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“liar, liar pants on fire”: A new benchmark dataset for fake news detection
William Yang Wang. 2017 · 2017
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Crowdsourcing multiple choice science questions
Johannes Welbl, Nelson F. Liu, and Matt Gardner. 2017 · 2017
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Seq2sql: Generating structured queries from natural language usin
Victor Zhong, Caiming Xiong, and Richard Socher. 2017 · 2017
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Learning to split and rephrase from Wikipedia edit history
Jan A. Botha, Manaal Faruqui, John Alex, Jason Baldridge, and Dipanjan Das. 2018 · 2018
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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. 2018 · 2018
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Hate speech dataset from a white supremacy forum
Ona de Gibert, Naiara Perez, Aitor García-Pablos, and Montse Cuadros. 2018 · 2018
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T-REx: A large scale alignment of natural language with knowledge base triples
Hady Elsahar, Pavlos Vougiouklis, Arslen Remaci, Christophe Gravier, Jonathon Hare, Frederique Laforest, and Elena Simperl. 2018 · 2018
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Identifying well-formed natural language questions
Manaal Faruqui and Dipanjan Das. 2018 · 2018
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Conditional neural processes
Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Rezende, and SM Ali Eslami. 2018 · 2018
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Meta-learning for low-resource neural machine translation
Jiatao Gu, Yong Wang, Yun Chen, Victor O. K. Li, and Kyunghyun Cho. 2018 · 2018
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FewRel: A large-scale supervised few-shot relation classification dataset with state-of-the-art evaluation
Xu Han, Hao Zhu, Pengfei Yu, Ziyun Wang, Yuan Yao, Zhiyuan Liu, and Maosong Sun. 2018 · 2018
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Few-shot charge prediction with discriminative legal attributes
Zikun Hu, Xiang Li, Cunchao Tu, Zhiyuan Liu, and Maosong Sun. 2018 · 2018
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Looking beyond the surface: A challenge set for reading comprehension over multiple sentences
Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, and Dan Roth. 2018 · 2018
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Scitail: A textual entailment dataset from science question answering
Tushar Khot, Ashish Sabharwal, and Peter Clark. 2018 · 2018
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Can a suit of armor conduct electricity? a new dataset for open book question answering
Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. 2018 · 2018
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TweetEval: Unified benchmark and comparative evaluation for tweet classification
Francesco Barbieri, Jose Camacho-Collados, Luis Espinosa Anke, and Leonardo Neves. 2020 · 2020
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Beat the AI: Investigating adversarial human annotation for reading comprehension
Max Bartolo, Alastair Roberts, Johannes Welbl, Sebastian Riedel, and Pontus Stenetorp. 2020 · 2020
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Abductive commonsense reasoning
Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Wen tau Yih, and Yejin Choi. 2020 · 2020
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PIQA: reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan LeBras, Jianfeng Gao, and Yejin Choi. 2020 · 2020
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ProtoQA: A question answering dataset for prototypical common-sense reasoning
Michael Boratko, Xiang Li, Tim O’Gorman, Rajarshi Das, Dan Le, and Andrew McCallum. 2020 · 2020
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Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, and Pieter Abbeel. 2018 · 2018
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
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On first-order meta-learning algorithms
Alex Nichol, Joshua Achiam, and John Schulman. 2018 · 2018
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DuoRC: Towards complex language understanding with paraphrased reading comprehension
Amrita Saha, Rahul Aralikatte, Mitesh M. Khapra, and Karthik Sankaranarayanan. 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
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Low-resource domain adaptation for compositional task-oriented semantic parsing
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Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG Challenge
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Neural snowball for few-shot relation learning
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Qasc: A dataset for question answering via sentence composition
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Explainable automated fact-checking for public health claims
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CommonGen: A constrained text generation challenge for generative commonsense reasoning
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How can we accelerate progress towards human-like linguistic generalization?
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“I’d rather just go to bed”: Understanding indirect answers
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AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
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BLiMP: The benchmark of linguistic minimal pairs for English
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Transformers: State-of-the-art natural language processing
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Semi-supervised URL segmentation with recurrent neural networks pre-trained on knowledge graph entities
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Making pre-trained language models better few-shot learners
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Beyond reptile: Meta-learned dot-product maximization between gradients for improved single-task regularization
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How many data points is a prompt worth?
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The power of scale for parameter-efficient prompt tuning
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Prefix-tuning: Optimizing continuous prompts for generation
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Gradient projection memory for continual learning
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Exploiting cloze-questions for few-shot text classification and natural language inference
Timo Schick and Hinrich Schütze. 2021 · 2021
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CrossFit: A few-shot learning challenge for cross-task generalization in NLP
Qinyuan Ye, Bill Yuchen Lin, and Xiang Ren. 2021 · 2021
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Calibrate before use: Improving few-shot performance of language models
Zihao Zhao, Eric Wallace, Shi Feng, Dan Klein, and Sameer Singh. 2021 · 2021
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Adapting language models for zero-shot learning by meta-tuning on dataset and prompt collections
Ruiqi Zhong, Kristy Lee, Zheng Zhang, and Dan Klein. 2021 · 2021
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Meta-learning via language model in-context tuning
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, and He He. 2022 · 2022
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Deep multi-task and meta learning
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PPT: Pre-trained prompt tuning for few-shot learning
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Learning a better initialization for soft prompts via meta-learning
Yukun Huang, Kun Qian, and Zhou Yu. 2022 · 2022
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SPoT: Better frozen model adaptation through soft prompt transfer
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Efficiently tuned parameters are task embeddings
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Prompt-aligned gradient for prompt tuning
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Is GPT-3 a good data annotator?
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