Fetching the paper…
Reading the bibliography…
Knowledge concept tagging for questions plays a crucial role in contemporary intelligent educational applications, including learning progress diagnosis, practice question recommendations, and course content organization.
Intelligent tutoring systems: an introduction
Hugh L Burns and Charles G Capps · 2013
Earlier work this paper cites.
A matrix factorization method for mapping items to skills and for enhancing expert-based q-matrices
M. C. Desmarais and R. Naceur · 2013
Earlier work this paper cites.
A tag based learning approach to knowledge acquisition for constructing prior knowledge and enhancing student reading comprehension
Jun-Ming Chen, Meng-Chang Chen, and Yeali S Sun · 2014
Earlier work this paper cites.
Bayesian estimation of the dina q matrix
Y. Chen, S. A. Culpepper, Y. Chen, and J. Douglas · 2018
Earlier work this paper cites.
Automatic question tagging with deep neural networks
Bo Sun, Yunzong Zhu, Yongkang Xiao, Rong Xiao, and Yungang Wei · 2018
Earlier work this paper cites.
Hierarchical multi-label text classification: An attention-based recurrent network approach
Wei Huang, Enhong Chen, Qi Liu, Yuying Chen, Zai Huang, Yang Liu, Zhou Zhao, Dan Zhang, and Shijin Wang · 2019
Earlier work this paper cites.
Ekt: Exercise-aware knowledge tracing for student performance prediction, 2019
Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen, Hui Xiong, Yu Su, and Guoping Hu · 2019
Earlier work this paper cites.
Automatic question tagging with deep neural networks
Bo Sun, Yunzong Zhu, Yongkang Xiao, Rong Xiao, and Yungang Wei · 2019
Earlier work this paper cites.
Quesnet: A unified representation for heterogeneous test questions
Yu Yin, Qi Liu, Zhenya Huang, Enhong Chen, Wei Tong, Shijin Wang, and Yu Su · 2019
Earlier work this paper cites.
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
Earlier work this paper cites.
Neural mathematical solver with enhanced formula structure
Zhenya Huang, Qi Liu, Weibo Gao, Jinze Wu, Yu Yin, Hao Wang, and Enhong Chen · 2020
Earlier work this paper cites.
Application of the lda model to semantic annotation of web-based english educational resources
Wei Du, Haiyan Zhu, and Teeraporn Saeheaw · 2021
Earlier work this paper cites.
Context-aware knowledge tracing integrated with the exercise representation and association in mathematics
T. Huang, M. Liang, H. Yang, Z. Li, T. Yu, and S. Hu · 2021
Earlier work this paper cites.
Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le · 2021
Cited alongside, same era.
Docent: Learning self-supervised entity representations from large document collections, 2021
Yury Zemlyanskiy, Sudeep Gandhe, Ruining He, Bhargav Kanagal, Anirudh Ravula, Juraj Gottweis, Fei Sha, and Ilya Eckstein · 2021
Cited alongside, same era.
Question tagging via graph-guided ranking
Xiao Zhang, Meng Liu, Jianhua Yin, Zhaochun Ren, and Liqiang Nie · 2021
Cited alongside, same era.
Structured information extraction from complex scientific text with fine-tuned large language models, 2022
Alexander Dunn, John Dagdelen, Nicholas Walker, Sanghoon Lee, Andrew S. Rosen, Gerbrand Ceder, Kristin Persson, and Anubhav Jain · 2022
Cited alongside, same era.
Selective annotation makes language models better few-shot learners
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, et al · 2023
Later among the works it cites.
Exploring the in-context learning ability of large language model for biomedical concept linking, 2023
Qinyong Wang, Zhenxiang Gao, and Rong Xu · 2023
Later among the works it cites.
Larger language models do in-context learning differently
Jerry Wei, Jason Wei, Yi Tay, Dustin Tran, Albert Webson, Yifeng Lu, Xinyun Chen, Hanxiao Liu, Da Huang, Denny Zhou, et al · 2023
Later among the works it cites.
Instructed language models with retrievers are powerful entity linkers, 2023
Zilin Xiao, Ming Gong, Jie Wu, Xingyao Zhang, Linjun Shou, Jian Pei, and Daxin Jiang · 2023
Later among the works it cites.
Biomedical entity linking with triple-aware pre-training, 2023
Xi Yan, Cedric Möller, and Ricardo Usbeck · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Hongjin Su, Jungo Kasai, Chen Henry Wu, Weijia Shi, Tianlu Wang, Jiayi Xin, Rui Zhang, Mari Ostendorf, Luke Zettlemoyer, Noah A Smith, et al · 2022
Cited alongside, same era.
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
Cited alongside, same era.
Rraml: Reinforced retrieval augmented machine learning, 2023
Andrea Bacciu, Florin Cuconasu, Federico Siciliano, Fabrizio Silvestri, Nicola Tonellotto, and Giovanni Trappolini · 2023
Cited alongside, same era.
Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al · 2023
Cited alongside, same era.
Pqsct: Pseudo-siamese bert for concept tagging with both questions and solutions
Tao Huang, Shengze Hu, Huali Yang, Jing Geng, Sannyuya Liu, Hao Zhang, and Zongkai Yang · 2023
Cited alongside, same era.
Pqsct: Pseudo-siamese bert for concept tagging with both questions and solutions
Tao Huang, Shengze Hu, Huali Yang, Jing Geng, Sannyuya Liu, Hao Zhang, and Zongkai Yang · 2023
Cited alongside, same era.
Active learning principles for in-context learning with large language models
Katerina Margatina, Timo Schick, Nikolaos Aletras, and Jane Dwivedi-Yu · 2023
Cited alongside, same era.
Optimal strategies to perform multilingual analysis of social content for a novel dataset in the tourism domain, 2023
Maxime Masson, Rodrigo Agerri, Christian Sallaberry, Marie-Noelle Bessagnet, Annig Le Parc Lacayrelle, and Philippe Roose · 2023
Cited alongside, same era.
Later among the works it cites.
Bingsheng Yao, Guiming Chen, Ruishi Zou, Yuxuan Lu, Jiachen Li, Shao Zhang, Sijia Liu, James Hendler, and Dakuo Wang · 2023
Later among the works it cites.
Expel: Llm agents are experiential learners
Andrew Zhao, Daniel Huang, Quentin Xu, Matthieu Lin, Yong-Jin Liu, and Gao Huang · 2023
Later among the works it cites.
Chatel: Entity linking with chatbots, 2024
Yifan Ding, Qingkai Zeng, and Tim Weninger · 2024
Closest in time.
A language model based framework for new concept placement in ontologies, 2024
Hang Dong, Jiaoyan Chen, Yuan He, Yongsheng Gao, and Ian Horrocks · 2024
Closest in time.
Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al · 2024
Closest in time.
Gumsley: Evaluating entity salience in summarization for 12 english genres, 2024
Jessica Lin and Amir Zeldes · 2024
Closest in time.
Internlm-math: Open math large language models toward verifiable reasoning
Huaiyuan Ying, Shuo Zhang, Linyang Li, Zhejian Zhou, Yunfan Shao, Zhaoye Fei, Yichuan Ma, Jiawei Hong, Kuikun Liu, Ziyi Wang, et al · 2024
Closest in time.