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Catastrophic Forgetting (CF) means models forgetting previously acquired knowledge when learning new data.
The third pascal recognizing textual entailment challenge
Danilo Giampiccolo, Bernardo Magnini, Ido Dagan, and William B Dolan. 2007 · 2007
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Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data
Gintare Karolina Dziugaite and Daniel M. Roy. 2017 · 2017
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On large-batch training for deep learning: Generalization gap and sharp minima
Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, and Ping Tak Peter Tang. 2017 · 2017
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al. 2017 · 2017
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RACE: large-scale reading comprehension dataset from examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard H. Hovy. 2017 · 2017
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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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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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Boolq: Exploring the surprising difficulty of natural yes/no questions
Clark, Christopher, Lee, Kenton, Chang, Ming-Wei, Kwiatkowski, Tom, Collins, Michael, and Kristina Toutanova. 2019 · 2019
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Visualizing and understanding the effectiveness of bert
Yaru Hao, Li Dong, Furu Wei, and Ke Xu. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Socialiqa: Commonsense reasoning about social interactions
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan LeBras, and Yejin Choi. 2019 · 2019
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Superglue: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019 · 2019
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Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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Fernando Alva-Manchego, Louis Martin, Antoine Bordes, Carolina Scarton, Benoît Sagot, and Lucia Specia. 2020 · 2020
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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 · 2020
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Neural crf model for sentence alignment in text simplification
Chao Jiang, Mounica Maddela, Wuwei Lan, Yang Zhong, and Wei Xu. 2020 · 2020
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021
Cited alongside, same era.
Progressive multi-granularity training for non-autoregressive translation
Liang Ding, Longyue Wang, Xuebo Liu, Derek F Wong, Dacheng Tao, and Zhaopeng Tu. 2021 · 2021
Cited alongside, same era.
Sharpness-aware minimization for efficiently improving generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, and Behnam Neyshabur. 2021 · 2021
Cited alongside, same era.
Self-guided curriculum learning for neural machine translation
Lei Zhou, Liang Ding, Kevin Duh, Shinji Watanabe, Ryohei Sasano, and Koichi Takeda. 2021 · 2021
Cited alongside, same era.
Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity
William Fedus, Barret Zoph, and Noam Shazeer. 2022 · 2022
Cited alongside, same era.
Yong Lin, Lu Tan, Hangyu Lin, Zeming Zheng, Renjie Pi, Jipeng Zhang, Shizhe Diao, Haoxiang Wang, Han Zhao, Yuan Yao, et al. 2023 · 2023
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Qingyu Lu, Baopu Qiu, Liang Ding, Kanjian Zhang, Tom Kocmi, and Dacheng Tao. 2023 · 2023
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Towards making the most of chatgpt for machine translation
Keqin Peng, Liang Ding, Qihuang Zhong, Li Shen, Xuebo Liu, Min Zhang, Yuanxin Ouyang, and Dacheng Tao. 2023 · 2023
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Detecting pretraining data from large language models
Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, and Luke Zettlemoyer. 2023 · 2023
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Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto. 2023 · 2023
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Csl: A large-scale chinese scientific literature dataset
Yudong Li, Yuqing Zhang, Zhe Zhao, Linlin Shen, Weijie Liu, Weiquan Mao, and Hui Zhang. 2022 · 2022
Cited alongside, same era.
Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2022 · 2022
Cited alongside, same era.
Fine-tuned language models are continual learners
Thomas Scialom, Tuhin Chakrabarty, and Smaranda Muresan. 2022 · 2022
Cited alongside, same era.
On the complementarity between pre-training and random-initialization for resource-rich machine translation
Changtong Zan, Liang Ding, Li Shen, Yu Cao, Weifeng Liu, and Dacheng Tao. 2022 · 2022
Cited alongside, same era.
Improving sharpness-aware minimization with fisher mask for better generalization on language models
Qihuang Zhong, Liang Ding, Li Shen, Peng Mi, Juhua Liu, Bo Du, and Dacheng Tao. 2022 · 2022
Cited alongside, same era.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al. 2023 · 2023
Cited alongside, same era.
Measuring and mitigating local instability in deep neural networks
Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, and Aram Galstyan. 2023 · 2023
Cited alongside, same era.
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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 · 2023
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Data augmented flatness-aware gradient projection for continual learning
Enneng Yang, Li Shen, Zhenyi Wang, Shiwei Liu, Guibing Guo, and Xingwei Wang. 2023 · 2023
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Metamath: Bootstrap your own mathematical questions for large language models
Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T Kwok, Zhenguo Li, Adrian Weller, and Weiyang Liu. 2023 · 2023
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Agenttuning: Enabling generalized agent abilities for llms
Aohan Zeng, Mingdao Liu, Rui Lu, Bowen Wang, Xiao Liu, Yuxiao Dong, and Jie Tang. 2023 · 2023
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Can chatgpt understand too? a comparative study on chatgpt and fine-tuned bert
Qihuang Zhong, Liang Ding, Juhua Liu, Bo Du, and Dacheng Tao. 2023 · 2023
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Deepseek llm: Scaling open-source language models with longtermism
Xiao Bi, Deli Chen, Guanting Chen, Shanhuang Chen, Damai Dai, Chengqi Deng, Honghui Ding, Kai Dong, Qiushi Du, Zhe Fu, et al. 2024 · 2024
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From mnist to imagenet and back: benchmarking continual curriculum learning
Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, and Roberto Corizzo. 2024 · 2024
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Healthcare copilot: Eliciting the power of general llms for medical consultation
Zhiyao Ren, Yibing Zhan, Baosheng Yu, Liang Ding, and Dacheng Tao. 2024 · 2024
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Adasam: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks
Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, and Dacheng Tao. 2024 · 2024
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Tinyllama: An open-source small language model
Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, and Wei Lu. 2024 · 2024
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