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Machine learning models for text classification often excel on in-distribution (ID) data but struggle with unseen out-of-distribution (OOD) inputs.
Semi-supervised learning by entropy minimization
Yves Grandvalet and Yoshua Bengio · 2004
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Sentence simplification for semantic role labeling
David Vickrey and Daphne Koller · 2008
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Hidden factors and hidden topics: understanding rating dimensions with review text
Julian McAuley and Jure Leskovec · 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, A. Ng, and Christopher Potts · 2013
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Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Jake Zhao, and Yann LeCun · 2015
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Deep Learning
Ian J. Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
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Semeval-2016 task 4: Sentiment analysis in twitter
Preslav Nakov, Alan Ritter, Sara Rosenthal, Fabrizio Sebastiani, and Veselin Stoyanov · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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Pixeldefend: Leveraging generative models to understand and defend against adversarial examples
Yang Song, Taesup Kim, Sebastian Nowozin, Stefano Ermon, and Nate Kushman · 2017
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Test-time data augmentation for estimation of heteroscedastic aleatoric uncertainty in deep neural networks
Murat Seçkin Ayhan and Philipp Berens · 2018
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Understanding back-translation at scale
Sergey Edunov, Myle Ott, Michael Auli, and David Grangier · 2018
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Iterative back-translation for neural machine translation
Cong Duy Vu Hoang, Philipp Koehn, Gholamreza Haffari, and Trevor Cohn · 2018
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Sequence-to-sequence data augmentation for dialogue language understanding
Yutai Hou, Yijia Liu, Wanxiang Che, and Ting Liu · 2018
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder · 2018
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Contextual augmentation: Data augmentation by words with paradigmatic relations
Sosuke Kobayashi · 2018
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Deflecting adversarial attacks with pixel deflection
Aaditya (Adi) Prakash, Nick Moran, Solomon Garber, Antonella DiLillo, and James A. Storer · 2018
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Qanet: Combining local convolution with global self-attention for reading comprehension
Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, and Quoc V. Le · 2018
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Do not have enough data? deep learning to the rescue!
Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich, Amir Kantor, George Kour, Segev Shlomov, N. Tepper, and Naama Zwerdling · 2019
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Nuanced metrics for measuring unintended bias with real data for text classification
Daniel Borkan, Lucas Dixon, Jeffrey Scott Sorensen, Nithum Thain, and Lucy Vasserman · 2019
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What does bert look at? an analysis of bert’s attention
Kevin Clark, Urvashi Khandelwal, Omer Levy, and Christopher D. Manning · 2019
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Certified adversarial robustness via randomized smoothing
Jeremy M. Cohen, Elan Rosenfeld, and J. Zico Kolter · 2019
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Machine learning for email spam filtering: review, approaches and open research problems
Emmanuel Gbenga Dada, Joseph Stephen Bassi, Haruna Chiroma, Shafi’i Muhammad Abdulhamid, Adebayo Olusola Adetunmbi, and Opeyemi Emmanuel Ajibuwa · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas G. Dietterich · 2019
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Training on synthetic noise improves robustness to natural noise in machine translation
Vladimir Karpukhin, Omer Levy, Jacob Eisenstein, and Marjan Ghazvininejad · 2019
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Domain adaptation with bert-based domain classification and data selection
Xiaofei Ma, Peng Xu, Zhiguo Wang, and Ramesh Nallapati · 2019
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Test-time augmentation for deep learning-based cell segmentation on microscopy images
Nikita Moshkov, Botond Mathe, Attila Kertész-Farkas, Réka Hollandi, and Péter Horváth · 2019
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Facebook fair’s wmt19 news translation task submission
Nathan Ng, Kyra Yee, Alexei Baevski, Myle Ott, Michael Auli, and Sergey Edunov · 2019
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Transfer learning in natural language processing
Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, and Thomas Wolf · 2019
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
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A survey on image data augmentation for deep learning
Connor Shorten and Taghi M. Khoshgoftaar · 2019
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Eda: Easy data augmentation techniques for boosting performance on text classification tasks
Jason Wei and Kai Zou · 2019
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Paraphrasing with large language models
Sam Witteveen and Martin Andrews · 2019
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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
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Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard H. Hovy, Minh-Thang Luong, and Quoc V. Le · 2019
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Counterfactual data augmentation for mitigating gender stereotypes in languages with rich morphology
Ran Zmigrod, Sabrina J. Mielke, Hanna M. Wallach, and Ryan Cotterell · 2019
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Cut the carp: Fishing for zero-shot story evaluation
Shahbuland Matiana, Jr. Allen Richard Smith, Ryan Teehan, Louis Castricato, Stella Biderman, Leo Gao, and Spencer Frazier · 2021
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Sequence length is a domain: Length-based overfitting in transformer models
Dusan Varis and Ondrej Bojar · 2021
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Tent: Fully test-time adaptation by entropy minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, and Trevor Darrell · 2021
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Increasing robustness to spurious correlations using forgettable examples
Yadollah Yaghoobzadeh, Soroush Mehri, Remi Tachet, Timothy J. Hazen, and Alessandro Sordoni · 2021
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Memo: Test time robustness via adaptation and augmentation
Marvin Zhang, Sergey Levine, and Chelsea Finn · 2021
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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, et al · 2020
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The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Rose Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, Shawn Presser, and Connor Leahy · 2020
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Pretrained transformers improve out-of-distribution robustness
Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, Rishabh Krishnan, and Dawn Song · 2020
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Learning loss for test-time augmentation
Ildoo Kim, Younghoon Kim, and Sungwoong Kim · 2020
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Wilds: A benchmark of in-the-wild distribution shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, and Percy Liang · 2020
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Data augmentation using pre-trained transformer models
Varun Kumar, Ashutosh Choudhary, and Eunah Cho · 2020
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How effective is task-agnostic data augmentation for pretrained transformers?
S. Longpre, Yu Wang, and Christopher DuBois · 2020
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Challenges in automated debiasing for toxic language detection
Xuhui Zhou, Maarten Sap, Swabha Swayamdipta, Noah A. Smith, and Yejin Choi · 2021
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Augnet: Dynamic test-time augmentation via differentiable functions
Shohei Enomoto, Monikka Roslianna Busto, and Takeharu Eda · 2022
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A survey of adversarial defences and robustness in nlp
Shreyansh Goyal, Sumanth Doddapaneni, Mitesh M.Khapra, and Balaraman Ravindran · 2022
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Toxigen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection
Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, and Ece Kamar · 2022
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Improved text classification via test-time augmentation
Helen Shiyang Lu, Divya Shanmugam, Harini Suresh, and John V. Guttag · 2022
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Low-resource authorship style transfer with in-context learning
Ajay Patel, Nicholas Andrews, and Chris Callison-Burch · 2022
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Addressing distribution shift at test time in pre-trained language models
Ayush Singh and J. Ortega · 2022
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Mirac Suzgun, Luke Melas-Kyriazi, and Dan Jurafsky · 2022
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How large language models are transforming machine-paraphrase plagiarism
Jan Philip Wahle, Terry Ruas, Frederic Kirstein, and Bela Gipp · 2022
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Falcon-40B: an open large language model with state-of-the-art performance
Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Merouane Debbah, Etienne Goffinet, Daniel Heslow, Julien Launay, Quentin Malartic, Badreddine Noune, Baptiste Pannier, and Guilherme Penedo · 2023
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A comparative study and analysis on toxic comment classification
Ashish, Aakanksha Rani, and Hatesh Shyan · 2023
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Pythia: A suite for analyzing large language models across training and scaling
Stella Biderman, Hailey Schoelkopf, Quentin Anthony, Herbie Bradley, Kyle O’Brien, Eric Hallahan, Mohammad Aflah Khan, Shivanshu Purohit, USVSN Sai Prashanth, Edward Raff, et al · 2023
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Ján Cegin, Jakub Simko, and Peter Brusilovsky · 2023
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Align your prompts: Test-time prompting with distribution alignment for zero-shot generalization
Jameel Hassan, Hanan Gani, Noor Hussein, Muhammad Uzair Khattak, Muzammal Naseer, Fahad Shahbaz Khan, and Salman Khan · 2023
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Understanding the detrimental class-level effects of data augmentation
P. Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Ramakrishna Vedantam, Hamed Firooz, and Andrew Gordon Wilson · 2023
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Large language models are state-of-the-art evaluators of translation quality
Tom Kocmi and Christian Federmann · 2023
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A comprehensive survey on test-time adaptation under distribution shifts
Jian Liang, Ran He, and Tien-Ping Tan · 2023
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Conversation style transfer using few-shot learning
Shamik Roy, Raphael Shu, Nikolaos Pappas, Elman Mansimov, Yi Zhang, Saab Mansour, and Dan Roth · 2023
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Randomized positional encodings boost length generalization of transformers
Anian Ruoss, Gr’egoire Del’etang, Tim Genewein, Jordi Grau-Moya, R. Csordás, Mehdi Abbana Bennani, Shane Legg, and Joel Veness · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin R. Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Daniel M. Bikel, Lukas Blecher, Cristian Cantón Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony S. Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel M. Kloumann, A. V. 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, R. Subramanian, Xia Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zhengxu Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom · 2023
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Stta: enhanced text classification via selective test-time augmentation
Haoyu Xiong, Xinchun Zhang, Leixin Yang, Yu Xiang, and Yaping Zhang · 2023
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Change is hard: A closer look at subpopulation shift
Yuzhe Yang, Haoran Zhang, Dina Katabi, and Marzyeh Ghassemi · 2023
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Revisiting out-of-distribution robustness in nlp: Benchmark, analysis, and llms evaluations
Lifan Yuan, Yangyi Chen, Ganqu Cui, Hongcheng Gao, Fangyuan Zou, Xingyi Cheng, Heng Ji, Zhiyuan Liu, and Maosong Sun · 2023
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Multilingual machine translation with large language models: Empirical results and analysis
Wenhao Zhu, Hongyi Liu, Qingxiu Dong, Jingjing Xu, Lingpeng Kong, Jiajun Chen, Lei Li, and Shujian Huang · 2023
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The unreasonable effectiveness of easy training data for hard tasks
Peter Hase, Mohit Bansal, Peter Clark, and Sarah Wiegreffe · 2024
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Transformers can achieve length generalization but not robustly
Yongchao Zhou, Uri Alon, Xinyun Chen, Xuezhi Wang, Rishabh Agarwal, and Denny Zhou · 2024
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