Fetching the paper…
Reading the bibliography…
Large Language Models (LLMs) have shown remarkable capabilities in language understanding and generation.
Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Distilbert, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
Earlier work this paper cites.
Japanese and korean voice search
Mike Schuster and Kaisuke Nakajima. 2012 · 2012
Earlier work this paper cites.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
Earlier work this paper cites.
Subword regularization: Improving neural network translation models with multiple subword candidates
Taku Kudo. 2018 · 2018
Earlier work this paper cites.
Sentencepiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
Earlier work this paper cites.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
Language (technology) is power: A critical survey of “bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach. 2020 · 2020
Earlier work this paper cites.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, and Nick Ryder et al. 2020 · 2020
Earlier work this paper cites.
ELECTRA: pre-training text encoders as discriminators rather than generators
Kevin Clark, Minh-Thang Luong, Quoc V. Le, and Christopher D. Manning. 2020 · 2020
Earlier work this paper cites.
Thieves on sesame street! model extraction of bert-based apis
Kalpesh Krishna, Gaurav Singh Tomar, Ankur P. Parikh, Nicolas Papernot, and Mohit Iyyer. 2020 · 2020
Earlier work this paper cites.
ALBERT: A lite BERT for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
Earlier work this paper cites.
Multilingual denoising pre-training for neural machine translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020 · 2020
Earlier work this paper cites.
On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al. 2021 · 2021
Earlier work this paper cites.
Extracting training data from large language models
Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, and Colin Raffel. 2021 · 2021
Earlier work this paper cites.
Superbizarre is not superb: Derivational morphology improves BERT‘s interpretation of complex words
Valentin Hofmann, Janet Pierrehumbert, and Hinrich Schütze. 2021 · 2021
Earlier work this paper cites.
Concealed data poisoning attacks on NLP models
Eric Wallace, Tony Z. Zhao, Shi Feng, and Sameer Singh. 2021 · 2021
Earlier work this paper cites.
Prompt injection: Parameterization of fixed inputs
Eunbi Choi, Yongrae Jo, Joel Jang, and Minjoon Seo. 2022 · 2022
Earlier work this paper cites.
Knowledge neurons in pretrained transformers
Damai Dai, Li Dong, Yaru Hao, Zhifang Sui, Baobao Chang, and Furu Wei. 2022 · 2022
Cited alongside, same era.
Training compute-optimal large language models
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katie Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Jack W. Rae, Oriol Vinyals, and Laurent Sifre. 2022 · 2022
Cited alongside, same era.
An embarrassingly simple method to mitigate undesirable properties of pretrained language model tokenizers
Valentin Hofmann, Hinrich Schuetze, and Janet Pierrehumbert. 2022 · 2022
Cited alongside, same era.
Chatgpt makes medicine easy to swallow: An exploratory case study on simplified radiology reports
Katharina Jeblick, Balthasar Schachtner, Jakob Dexl, Andreas Mittermeier, Anna Theresa Stüber, Johanna Topalis, Tobias Weber, Philipp Wesp, Bastian O. Sabel, Jens Ricke, and Michael Ingrisch. 2022 · 2022
Cited alongside, same era.
Membership inference attacks against machine learning models via prediction sensitivity
Lan Liu, Yi Wang, Gaoyang Liu, Kai Peng, and Chen Wang. 2023 · 2023
Later among the works it cites.
On the educational impact of chatgpt: Is artificial intelligence ready to obtain a university degree?
Kamil Malinka, Martin Peresíni, Anton Firc, Ondrej Hujnak, and Filip Janus. 2023 · 2023
Later among the works it cites.
Codegen: An open large language model for code with multi-turn program synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. 2023 · 2023
Later among the works it cites.
OpenAI. 2023 · 2023
Later among the works it cites.
Does synthetic data generation of llms help clinical text mining?
Ruixiang Tang, Xiaotian Han, Xiaoqian Jiang, and Xia Hu. 2023 · 2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Electrochemical characterization of ionic dynamics resulting from spin conversion of water isomers
Serge Kernbach. 2022 · 2022
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 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.
Law informs code: A legal informatics approach to aligning artificial intelligence with humans
John J. Nay. 2022 · 2022
Cited alongside, same era.
Chatgpt: The end of online exam integrity?
Teo Susnjak. 2022 · 2022
Cited alongside, same era.
Galactica: A large language model for science
Ross Taylor, Marcin Kardas, Guillem Cucurull, Thomas Scialom, Anthony Hartshorn, Elvis Saravia, Andrew Poulton, Viktor Kerkez, and Robert Stojnic. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou. 2022 · 2022
Cited alongside, same era.
Legal prompting: Teaching a language model to think like a lawyer
Fangyi Yu, Lee Quartey, and Frank Schilder. 2022 · 2022
Cited alongside, same era.
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, and Kevin Stone et al. 2023 · 2023
Later among the works it cites.
Instructions as backdoors: Backdoor vulnerabilities of instruction tuning for large language models
Jiashu Xu, Mingyu Derek Ma, Fei Wang, Chaowei Xiao, and Muhao Chen. 2023 · 2023
Later among the works it cites.
Baichuan 2: Open large-scale language models
Aiyuan Yang, Bin Xiao, and Bingning Wang et al. 2023 · 2023
Later among the works it cites.
GLM-130B: an open bilingual pre-trained model
Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, Weng Lam Tam, Zixuan Ma, Yufei Xue, Jidong Zhai, Wenguang Chen, Zhiyuan Liu, Peng Zhang, Yuxiao Dong, and Jie Tang. 2023 · 2023
Later among the works it cites.
Least-to-most prompting enables complex reasoning in large language models
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, and Ed H. Chi. 2023 · 2023
Later among the works it cites.
Breaking down the defenses: A comparative survey of attacks on large language models
Arijit Ghosh Chowdhury, Md Mofijul Islam, Vaibhav Kumar, Faysal Hossain Shezan, Vaibhav Kumar, Vinija Jain, and Aman Chadha. 2024 · 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, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2024 · 2024
Closest in time.
Fishing for magikarp: Automatically detecting under-trained tokens in large language models
Sander Land and Max Bartolo. 2024 · 2024
Closest in time.
OpenAI. 2024 · 2024
Closest in time.
Qwen Team. 2024 · 2024
Closest in time.
Yi: Open foundation models by 01.ai
Alex Young, Bei Chen, Chao Li, Chengen Huang, Ge Zhang, Guanwei Zhang, Heng Li, Jiangcheng Zhu, Jianqun Chen, Jing Chang, Kaidong Yu, Peng Liu, Qiang Liu, Shawn Yue, Senbin Yang, Shiming Yang, Tao Yu, Wen Xie, Wenhao Huang, Xiaohui Hu, Xiaoyi Ren, Xinyao Niu, Pengcheng Nie, Yuchi Xu, Yudong Liu, Yue Wang, Yuxuan Cai, Zhenyu Gu, Zhiyuan Liu, and Zonghong Dai. 2024 · 2024
Closest in time.
Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
DeepSeek-AI. 2025 · 2025
Closest in time.
A comprehensive survey of attack techniques, implementation, and mitigation strategies in large language models
Aysan Esmradi, Daniel Wankit Yip, and Chun-Fai Chan. 2023 · 2034
Closest in time.