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Low-rank adaptation is a popular parameter-efficient fine-tuning method for large language models.
Www’18 open challenge: financial opinion mining and question answering
Macedo Maia, Siegfried Handschuh, André Freitas, Brian Davis, Ross McDermott, Manel Zarrouk, and Alexandra Balahur. 2018 · 1942
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Glu variants improve transformer
Noam Shazeer. 2020 · 2002
Earlier work this paper cites.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2020 · 2009
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Good debt or bad debt: Detecting semantic orientations in economic texts
Pekka Malo, Ankur Sinha, Pekka Korhonen, Jyrki Wallenius, and Pyry Takala. 2014 · 2014
Earlier work this paper cites.
Domain adaption of named entity recognition to support credit risk assessment
Julio Cesar Salinas Alvarado, Karin Verspoor, and Timothy Baldwin. 2015 · 2015
Earlier work this paper cites.
Pubmed 200k rct: a dataset for sequential sentence classification in medical abstracts
Franck Dernoncourt and Ji Young Lee. 2017 · 2017
Earlier work this paper cites.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman. 2018 · 2018
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Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
Earlier work this paper cites.
Pubmedqa: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu. 2019 · 2019
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Root mean square layer normalization
Biao Zhang and Rico Sennrich. 2019 · 2019
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The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al. 2020 · 2020
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
Earlier work this paper cites.
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, et al. 2021 · 2021
Earlier work this paper cites.
Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
Cited alongside, same era.
What disease does this patient have? a large-scale open domain question answering dataset from medical exams
Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits. 2021 · 2021
Cited alongside, same era.
The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
Cited alongside, same era.
Impact of news on the commodity market: Dataset and results
Ankur Sinha and Tanmay Khandait. 2021 · 2021
Cited alongside, same era.
Convfinqa: Exploring the chain of numerical reasoning in conversational finance question answering
Chipnemo: Domain-adapted llms for chip design
Mingjie Liu, Teodor-Dumitru Ene, Robert Kirby, Chris Cheng, Nathaniel Pinckney, Rongjian Liang, Jonah Alben, Himyanshu Anand, Sanmitra Banerjee, Ismet Bayraktaroglu, et al. 2023 · 2023
Later among the works it cites.
Tied-lora: Enhacing parameter efficiency of lora with weight tying
Adithya Renduchintala, Tugrul Konuk, and Oleksii Kuchaiev. 2023 · 2023
Later among the works it cites.
Bloomberggpt: A large language model for finance
Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann. 2023 · 2023
Later among the works it cites.
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
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
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Zhiyu Chen, Shiyang Li, Charese Smiley, Zhiqiang Ma, Sameena Shah, and William Yang Wang. 2022 · 2022
Cited alongside, same era.
Disc-finllm: A chinese financial large language model based on multiple experts fine-tuning
Wei Chen, Qiushi Wang, Zefei Long, Xianyin Zhang, Zhongtian Lu, Bingxuan Li, Siyuan Wang, Jiarong Xu, Xiang Bai, Xuanjing Huang, et al. 2023 · 2023
Cited alongside, same era.
Adapting large language models via reading comprehension
Daixuan Cheng, Shaohan Huang, and Furu Wei. 2023 · 2023
Cited alongside, same era.
Evaluating language models for mathematics through interactions
Katherine M Collins, Albert Q Jiang, Simon Frieder, Lionel Wong, Miri Zilka, Umang Bhatt, Thomas Lukasiewicz, Yuhuai Wu, Joshua B Tenenbaum, William Hart, et al. 2023 · 2023
Cited alongside, same era.
Specializing smaller language models towards multi-step reasoning
Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, and Tushar Khot. 2023 · 2023
Cited alongside, same era.
Medalpaca–an open-source collection of medical conversational ai models and training data
Tianyu Han, Lisa C Adams, Jens-Michalis Papaioannou, Paul Grundmann, Tom Oberhauser, Alexander Löser, Daniel Truhn, and Keno K Bressem. 2023 · 2023
Cited alongside, same era.
Mathprompter: Mathematical reasoning using large language models
Shima Imani, Liang Du, and Harsh Shrivastava. 2023 · 2023
Cited alongside, same era.
Camels in a changing climate: Enhancing lm adaptation with tulu 2
Hamish Ivison, Yizhong Wang, Valentina Pyatkin, Nathan Lambert, Matthew Peters, Pradeep Dasigi, Joel Jang, David Wadden, Noah A Smith, Iz Beltagy, et al. 2023 · 2023
Cited alongside, same era.
Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2024 · 2024
Closest in time.
LoRA+: Efficient Low Rank Adaptation of Large Models
Soufiane Hayou, Nikhil Ghosh, and Bin Yu. 2024 · 2024
Closest in time.
Dora: Weight-decomposed low-rank adaptation
Shih-Yang Liu, Chien-Yi Wang, Hongxu Yin, Pavlo Molchanov, Yu-Chiang Frank Wang, Kwang-Ting Cheng, and Min-Hung Chen. 2024 · 2024
Closest in time.
Periodiclora: Breaking the low-rank bottleneck in lora optimization
Xiangdi Meng, Damai Dai, Weiyao Luo, Zhe Yang, Shaoxiang Wu, Xiaochen Wang, Peiyi Wang, Qingxiu Dong, Liang Chen, and Zhifang Sui. 2024 · 2024
Closest in time.
Reslora: Identity residual mapping in low-rank adaption
Shuhua Shi, Shaohan Huang, Minghui Song, Zhoujun Li, Zihan Zhang, Haizhen Huang, Furu Wei, Weiwei Deng, Feng Sun, and Qi Zhang. 2024 · 2024
Closest in time.
Roformer: Enhanced transformer with rotary position embedding
Jianlin Su, Murtadha Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu. 2024 · 2024
Closest in time.
How far can camels go? exploring the state of instruction tuning on open resources
Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Chandu, David Wadden, Kelsey MacMillan, Noah A Smith, Iz Beltagy, et al. 2024 · 2024
Closest in time.
Lima: Less is more for alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, et al. 2024 · 2024
Closest in time.
Asymmetry in low-rank adapters of foundation models
Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, and Justin Solomon. 2024 · 2024
Closest in time.