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Due to the widespread use of LLMs and the rising critical ethical and safety concerns, LLM unlearning methods have been developed to remove harmful knowledge and undesirable capabilities.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Random-walk computation of similarities between nodes of a graph with application to collaborative recommendation
Francois Fouss, Alain Pirotte, Jean-Michel Renders, and Marco Saerens · 2007
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Pearson correlation coefficient
Israel Cohen, Yiteng Huang, Jingdong Chen, Jacob Benesty, Jacob Benesty, Jingdong Chen, Yiteng Huang, and Israel Cohen · 2009
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Dina model and parameter estimation: A didactic
Jimmy De La Torre · 2009
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Addressing the assessment challenge with an online system that tutors as it assesses
Mingyu Feng, Neil Heffernan, and Kenneth Koedinger · 2009
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Bloom’s taxonomy
Mary Forehand · 2010
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Developing score reports for cognitive diagnostic assessments
Mary Roduta Roberts and Mark J Gierl · 2010
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Multidimensional item response theory models
Terry A Ackerman · 2014
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Engaging with massive online courses
Ashton Anderson, Daniel Huttenlocher, Jon Kleinberg, and Jure Leskovec · 2014
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Intelligent tutoring systems: Evolutions in design
Hugh Burns, Carol A Luckhardt, James W Parlett, and Carol L Redfield · 2014
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Fuzzy cognitive diagnosis for modelling examinee performance
Qi Liu, Runze Wu, Enhong Chen, Guandong Xu, Yu Su, Zhigang Chen, and Guoping Hu · 2018
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Mitre att&ck: Design and philosophy
Blake E Strom, Andy Applebaum, Doug P Miller, Kathryn C Nickels, Adam G Pennington, and Cody B Thomas · 2018
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Exploiting cognitive structure for adaptive learning
Qi Liu, Shiwei Tong, Chuanren Liu, Hongke Zhao, Enhong Chen, Haiping Ma, and Shijin Wang · 2019
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2020
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Neural cognitive diagnosis for intelligent education systems
Fei Wang, Qi Liu, Enhong Chen, Zhenya Huang, Yuying Chen, Yu Yin, Zai Huang, and Shijin Wang · 2020
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Exercise recommendation method combining neuralcd and neumf models
Yan Cheng, Meng Li, Haomai Chen, Yingying Cai, Huan Sun, Haifeng Zou, and Guanghe Zhang · 2021
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A system for automated open-source threat intelligence gathering and management
Peng Gao, Xiaoyuan Liu, Edward Choi, Bhavna Soman, Chinmaya Mishra, Kate Farris, and Dawn Song · 2021
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Threatkg: A threat knowledge graph for automated open-source cyber threat intelligence gathering and management, 2022
Peng Gao, Xiaoyuan Liu, Edward Choi, Sibo Ma, Xinyu Yang, Zhengjie Ji, Zilin Zhang, and Dawn Song · 2022
Cited alongside, same era.
Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Suchin Gururangan, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi · 2022
Cited alongside, same era.
Cognitive diagnostic assessment in university statistics education: valid and reliable skill measurement for actionable feedback using learning dashboards
Lientje Maas, Matthieu JS Brinkhuis, Liesbeth Kester, and Leoniek Wijngaards-de Meij · 2022
Cited alongside, same era.
Unrolling sgd: Understanding factors influencing machine unlearning
Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, and Nicolas Papernot · 2022
Cited alongside, same era.
Neuralcd: a general framework for cognitive diagnosis
Fei Wang, Qi Liu, Enhong Chen, Zhenya Huang, Yu Yin, Shijin Wang, and Yu Su · 2022
Autobench-v: Can large vision-language models benchmark themselves?
Han Bao, Yue Huang, Yanbo Wang, Jiayi Ye, Xiangqi Wang, Xiuying Chen, Mohamed Elhoseiny, and Xiangliang Zhang · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
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Scemqa: A scientific college entrance level multimodal question answering benchmark
Zhenwen Liang, Kehan Guo, Gang Liu, Taicheng Guo, Yujun Zhou, Tianyu Yang, Jiajun Jiao, Renjie Pi, Jipeng Zhang, and Xiangliang Zhang · 2024
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Inductive cognitive diagnosis for fast student learning in web-based intelligent education systems
Shuo Liu, Junhao Shen, Hong Qian, and Aimin Zhou · 2024
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al · 2023
Cited alongside, same era.
Who’s harry potter? approximate unlearning in llms
Ronen Eldan and Mark Russinovich · 2023
Cited alongside, same era.
Leveraging transferable knowledge concept graph embedding for cold-start cognitive diagnosis
Weibo Gao, Hao Wang, Qi Liu, Fei Wang, Xin Lin, Linan Yue, Zheng Zhang, Rui Lv, and Shijin Wang · 2023
Cited alongside, same era.
What can large language models do in chemistry? a comprehensive benchmark on eight tasks
Taicheng Guo, Bozhao Nan, Zhenwen Liang, Zhichun Guo, Nitesh Chawla, Olaf Wiest, Xiangliang Zhang, et al · 2023
Cited alongside, same era.
Trustgpt: A benchmark for trustworthy and responsible large language models
Yue Huang, Qihui Zhang, Lichao Sun, et al · 2023
Cited alongside, same era.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al · 2023
Cited alongside, same era.
Pratyush Maini, Zhili Feng, Avi Schwarzschild, Zachary C Lipton, and J Zico Kolter · 2024
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2024
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Optimization-based prompt injection attack to llm-as-a-judge
Jiawen Shi, Zenghui Yuan, Yinuo Liu, Yue Huang, Pan Zhou, Lichao Sun, and Neil Zhenqiang Gong · 2024
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Cs-bench: A comprehensive benchmark for large language models towards computer science mastery
Xiaoshuai Song, Muxi Diao, Guanting Dong, Zhengyang Wang, Yujia Fu, Runqi Qiao, Zhexu Wang, Dayuan Fu, Huangxuan Wu, Bin Liang, et al · 2024
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Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change
Karthik Valmeekam, Matthew Marquez, Alberto Olmo, Sarath Sreedharan, and Subbarao Kambhampati · 2024
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Evaluating copyright takedown methods for language models
Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, and Peter Henderson · 2024
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Unigen: A unified framework for textual dataset generation using large language models
Siyuan Wu, Yue Huang, Chujie Gao, Dongping Chen, Qihui Zhang, Yao Wan, Tianyi Zhou, Xiangliang Zhang, Jianfeng Gao, Chaowei Xiao, et al · 2024
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Cliperase: Efficient unlearning of visual-textual associations in clip
Tianyu Yang, Lisen Dai, Zheyuan Liu, Xiangqi Wang, Meng Jiang, Yapeng Tian, and Xiangliang Zhang · 2024
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Attack-free evaluating and enhancing adversarial robustness on categorical data
Yujun Zhou, Yufei Han, Haomin Zhuang, Hongyan Bao, and Xiangliang Zhang · 2024
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Dynamic evaluation of large language models by meta probing agents
Kaijie Zhu, Jindong Wang, Qinlin Zhao, Ruochen Xu, and Xing Xie · 2024
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Chongyu Fan, Jinghan Jia, Yihua Zhang, Anil Ramakrishna, Mingyi Hong, and Sijia Liu · 2025
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Can llms solve molecule puzzles? a multimodal benchmark for molecular structure elucidation
Kehan Guo, Bozhao Nan, Yujun Zhou, Taicheng Guo, Zhichun Guo, Mihir Surve, Zhenwen Liang, Nitesh Chawla, Olaf Wiest, and Xiangliang Zhang · 2025
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Position: We need an adaptive interpretation of helpful, honest, and harmless principles
Yue Huang, Chujie Gao, Yujun Zhou, Kehan Guo, Xiangqi Wang, Or Cohen-Sasson, Max Lamparth, and Xiangliang Zhang · 2025
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