Fetching the paper…
Reading the bibliography…
To obtain high-quality annotations under limited budget, semi-automatic annotation methods are commonly used, where a portion of the data is annotated by experts and a model is then trained to complete the annotations for the remaining data.
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 · 1901
Earlier work this paper cites.
The algorithmic automation problem: Prediction, triage, and human effort
Maithra Raghu, Katy Blumer, Greg Corrado, Jon Kleinberg, Ziad Obermeyer, and Sendhil Mullainathan. 2019 · 1903
Earlier work this paper cites.
Vinery: A visual ide for information extraction
Yunyao Li, Elmer Kim, Marc A Touchette, Ramiya Venkatachalam, and Hao Wang. 2015 · 1951
Earlier work this paper cites.
Sample selection for statistical grammar induction
Rebecca Hwa. 2000 · 2000
Earlier work this paper cites.
Learning with local and global consistency
Dengyong Zhou, Olivier Bousquet, Thomas Lal, Jason Weston, and Bernhard Schölkopf. 2003 · 2003
Earlier work this paper cites.
Interactive information extraction with constrained conditional random fields
Trausti Kristjansson, Aron Culotta, Paul Viola, and Andrew McCallum. 2004 · 2004
Earlier work this paper cites.
Worst-case analysis of selective sampling for linear classification
Nicolo Cesa-Bianchi, Claudio Gentile, Luca Zaniboni, and Manfred Warmuth. 2006 · 2006
Earlier work this paper cites.
Automatic image annotation using auxiliary text information
Yansong Feng and Mirella Lapata. 2008 · 2008
Earlier work this paper cites.
Robust bounds for classification via selective sampling
Nicolo Cesa-Bianchi, Claudio Gentile, and Francesco Orabona. 2009 · 2009
Earlier work this paper cites.
A survey of deep active learning
Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Xiaojiang Chen, and X. Wang. 2020 · 2009
Earlier work this paper cites.
Breaking the curse of kernelization: Budgeted stochastic gradient descent for large-scale svm training
Zhuang Wang, Koby Crammer, and Slobodan Vucetic. 2012 · 2012
Earlier work this paper cites.
Practical bilevel optimization: algorithms and applications , volume 30
Jonathan F Bard. 2013 · 2013
Earlier work this paper cites.
Collaborative topic regression with social regularization for tag recommendation
Hao Wang, Binyi Chen, and Wu-Jun Li. 2013 · 2013
Earlier work this paper cites.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
Earlier work this paper cites.
Inclusive yet selective: Supervised distributional hypernymy detection
Stephen Roller, Katrin Erk, and Gemma Boleda. 2014 · 2014
Earlier work this paper cites.
Ike-an interactive tool for knowledge extraction
Bhavana Dalvi, Sumithra Bhakthavatsalam, Chris Clark, Peter Clark, Oren Etzioni, Anthony Fader, and Dirk Groeneveld. 2016 · 2016
Earlier work this paper cites.
Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole. 2016 · 2016
Earlier work this paper cites.
Training region-based object detectors with online hard example mining
Abhinav Shrivastava, Abhinav Gupta, and Ross Girshick. 2016 · 2016
Earlier work this paper cites.
A curriculum learning method for improved noise robustness in automatic speech recognition
Stefan Braun, Daniel Neil, and Shih-Chii Liu. 2017 · 2017
Earlier work this paper cites.
Automatic annotation and evaluation of error types for grammatical error correction
Christopher Bryant, Mariano Felice, and Ted Briscoe. 2017 · 2017
Earlier work this paper cites.
On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger. 2017 · 2017
Earlier work this paper cites.
Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2017 · 2017
Earlier work this paper cites.
Decomposition of uncertainty in bayesian deep learning for efficient and risk-sensitive learning
Stefan Depeweg, Jose-Miguel Hernandez-Lobato, Finale Doshi-Velez, and Steffen Udluft. 2018 · 2018
Earlier work this paper cites.
To trust or not to trust a classifier
Heinrich Jiang, Been Kim, Melody Guan, and Maya Gupta. 2018 · 2018
Earlier work this paper cites.
The INCEpTION platform: Machine-assisted and knowledge-oriented interactive annotation
Jan-Christoph Klie, Michael Bugert, Beto Boullosa, Richard Eckart de Castilho, and Iryna Gurevych. 2018 · 2018
Cited alongside, same era.
Predict responsibly: improving fairness and accuracy by learning to defer
David Madras, Toni Pitassi, and Richard Zemel. 2018 · 2018
Cited alongside, same era.
Large margin few-shot learning
Yong Wang, Xiao-Ming Wu, Qimai Li, Jiatao Gu, Wangmeng Xiang, Lei Zhang, and Victor OK Li. 2018 · 2018
Cited alongside, same era.
Continuous quality control and advanced text segment annotation with WAT-SL 2.0
Christina Lohr, Johannes Kiesel, Stephanie Luther, Johannes Hellrich, Tobias Kolditz, Benno Stein, and Udo Hahn. 2019 · 2019
Cited alongside, same era.
On the calibration of multiclass classification with rejection
Chenri Ni, Nontawat Charoenphakdee, Junya Honda, and Masashi Sugiyama. 2019 · 2019
Cited alongside, same era.
Learning to complement humans
Bryan Wilder, Eric Horvitz, and Ece Kamar. 2021 · 2021
Later among the works it cites.
An interactive neural network approach to keyphrase extraction in talent recruitment
Kaichun Yao, Chuan Qin, Hengshu Zhu, Chao Ma, Jingshuai Zhang, Yi Du, and Hui Xiong. 2021 · 2021
Later among the works it cites.
A human-machine collaborative framework for evaluating malevolence in dialogues
Yangjun Zhang, Pengjie Ren, and Maarten de Rijke. 2021 · 2021
Later among the works it cites.
Ai assisted data labeling with interactive auto label
Michael Desmond, Michelle Brachman, Evelyn Duesterwald, Casey Dugan, Narendra Nath Joshi, Qian Pan, and Carolina Spina. 2022 · 2022
Later among the works it cites.
Fairness-aware selective sampling on attributed graphs
Oyku Deniz Kose and Yanning Shen. 2022 · 2022
Later among the works it cites.
Promptiverse: Scalable generation of scaffolding prompts through human-ai hybrid knowledge graph annotation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Analysis of automatic annotation suggestions for hard discourse-level tasks in expert domains
Claudia Schulz, Christian M Meyer, Jan Kiesewetter, Michael Sailer, Elisabeth Bauer, Martin R Fischer, Frank Fischer, and Iryna Gurevych. 2019 · 2019
Cited alongside, same era.
Learning emphasis selection for written text in visual media from crowd-sourced label distributions
Amirreza Shirani, Franck Dernoncourt, Paul Asente, Nedim Lipka, Seokhwan Kim, Jose Echevarria, and Thamar Solorio. 2019 · 2019
Cited alongside, same era.
Self-paced active learning: Query the right thing at the right time
Ying-Peng Tang and Sheng-Jun Huang. 2019 · 2019
Cited alongside, same era.
Semi-automated data labeling
Michael Desmond, Evelyn Duesterwald, Kristina Brimijoin, Michelle Brachman, and Qian Pan. 2021a · 2020
Cited alongside, same era.
Semi-automated data labeling
Michael Desmond, Evelyn Duesterwald, Kristina Brimijoin, Michelle Brachman, and Qian Pan. 2021b · 2020
Cited alongside, same era.
Active Learning for BERT: An Empirical Study
Liat Ein-Dor, Alon Halfon, Ariel Gera, Eyal Shnarch, Lena Dankin, Leshem Choshen, Marina Danilevsky, Ranit Aharonov, Yoav Katz, and Noam Slonim. 2020 · 2020
Cited alongside, same era.
Inconsistencies in crowdsourced slot-filling annotations: A typology and identification methods
Stefan Larson, Adrian Cheung, Anish Mahendran, Kevin Leach, and Jonathan K Kummerfeld. 2020 · 2020
Cited alongside, same era.
Yoonjoo Lee, John Joon Young Chung, Tae Soo Kim, Jean Y Song, and Juho Kim. 2022 · 2022
Later among the works it cites.
Prioritized training on points that are learnable, worth learning, and not yet learnt
Sören Mindermann, Jan M Brauner, Muhammed T Razzak, Mrinank Sharma, Andreas Kirsch, Winnie Xu, Benedikt Höltgen, Aidan N Gomez, Adrien Morisot, Sebastian Farquhar, et al. 2022 · 2022
Later among the works it cites.
Selective annotation makes language models better few-shot learners
Hongjin Su, Jungo Kasai, Chen Henry Wu, Weijia Shi, Tianlu Wang, Jiayi Xin, Rui Zhang, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, and Tao Yu. 2022 · 2022
Later among the works it cites.
Boosting active learning via improving test performance
Tianyang Wang, Xingjian Li, Pengkun Yang, Guosheng Hu, Xiangrui Zeng, Siyu Huang, Cheng-Zhong Xu, and Min Xu. 2022 · 2022
Later among the works it cites.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
Later among the works it cites.
Is GPT-3 a good data annotator?
Bosheng Ding, Chengwei Qin, Linlin Liu, Yew Ken Chia, Boyang Li, Shafiq Joty, and Lidong Bing. 2023 · 2023
Later among the works it cites.
Chatgpt outperforms crowd workers for text-annotation tasks
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli. 2023 · 2023
Later among the works it cites.
Annollm: Making large language models to be better crowdsourced annotators
Xingwei He, Zhenghao Lin, Yeyun Gong, A-Long Jin, Hang Zhang, Chen Lin, Jian Jiao, Siu Ming Yiu, Nan Duan, and Weizhu Chen. 2023 · 2023
Later among the works it cites.
Zero-shot clinical entity recognition using chatgpt
Yan Hu, Iqra Ameer, Xu Zuo, Xueqing Peng, Yujia Zhou, Zehan Li, Yiming Li, Jianfu Li, Xiaoqian Jiang, and Hua Xu. 2023 · 2023
Later among the works it cites.
Reduce human labor on evaluating conversational information retrieval system: A human-machine collaboration approach
Chen Huang, Peixin Qin, Wenqiang Lei, and Jiancheng Lv. 2023 · 2023
Later among the works it cites.
Minzhi Li, Taiwei Shi, Caleb Ziems, Min-Yen Kan, Nancy F. Chen, Zhengyuan Liu, and Diyi Yang. 2023 · 2023
Later among the works it cites.
A comprehensive evaluation of chatgpt’s zero-shot text-to-sql capability
Aiwei Liu, Xuming Hu, Lijie Wen, and Philip S Yu. 2023 · 2023
Later among the works it cites.
Zero is not hero yet: Benchmarking zero-shot performance of llms for financial tasks
Agam Shah and Sudheer Chava. 2023 · 2023
Later among the works it cites.
Evaluation of chatgpt as a question answering system for answering complex questions
Yiming Tan, Dehai Min, Yu Li, Wenbo Li, Nan Hu, Yongrui Chen, and Guilin Qi. 2023 · 2023
Later among the works it cites.
Is chatgpt a good nlg evaluator? a preliminary study
Jiaan Wang, Yunlong Liang, Fandong Meng, Zengkui Sun, Haoxiang Shi, Zhixu Li, Jinan Xu, Jianfeng Qu, and Jie Zhou. 2023 · 2023
Later among the works it cites.
FreeAL: Towards human-free active learning in the era of large language models
Ruixuan Xiao, Yiwen Dong, Junbo Zhao, Runze Wu, Minmin Lin, Gang Chen, and Haobo Wang. 2023 · 2023
Later among the works it cites.
Bingsheng Yao, Ishan Jindal, Lucian Popa, Yannis Katsis, Sayan Ghosh, Lihong He, Yuxuan Lu, Shashank Srivastava, James Hendler, and Dakuo Wang. 2023 · 2023
Later among the works it cites.
Data augmentation using llms: Data perspectives, learning paradigms and challenges
Bosheng Ding, Chengwei Qin, Ruochen Zhao, Tianze Luo, Xinze Li, Guizhen Chen, Wenhan Xia, Junjie Hu, Anh Tuan Luu, and Shafiq Joty. 2024 · 2024
Closest in time.
Does collaborative human-lm dialogue generation help information extraction from human dialogues?
Bo-Ru Lu, Nikita Haduong, Chia-Hsuan Lee, Zeqiu Wu, Hao Cheng, Paul Koester, Jean Utke, Tao Yu, Noah A. Smith, and Mari Ostendorf. 2024 · 2024
Closest in time.