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Large language models (LLMs) have recently transformed both the academic and industrial landscapes due to their remarkable capacity to understand, analyze, and generate texts based on their vast knowledge and reasoning ability.
Continual learning with hypernetworks
Johannes von Oswald, Christian Henning, Benjamin F. Grewe, and João Sacramento. 2022 · 1906
Earlier work this paper cites.
A simple neural network generating an interactive memory
James A Anderson. 1972 · 1972
Earlier work this paper cites.
Correlation matrix memories
Teuvo Kohonen. 1972 · 1972
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Building applied natural language generation systems
EHUD REITER and ROBERT DALE. 1997 · 1997
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database. In CVPR
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009 · 2009
Earlier work this paper cites.
Modifying Memories in Transformer Models
Chen Zhu, Ankit Singh Rawat, Manzil Zaheer, Srinadh Bhojanapalli, Daliang Li, Felix Yu, and Sanjiv Kumar. 2020 · 2012
Earlier work this paper cites.
Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
Earlier work this paper cites.
Vqa: Visual question answering. In ICCV
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C Lawrence Zitnick, and Devi Parikh. 2015 · 2015
Earlier work this paper cites.
Microsoft coco captions: Data collection and evaluation server. arXiv 2015
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick. 2015 · 2015
Earlier work this paper cites.
David Ha, Andrew Dai, and Quoc V. Le. 2016 · 2016
Earlier work this paper cites.
Deep residual learning for image recognition. In CVPR
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Earlier work this paper cites.
Optimization as a model for few-shot learning. In International conference on learning representations
Sachin Ravi and Hugo Larochelle. 2016 · 2016
Earlier work this paper cites.
Model-agnostic meta-learning for fast adaptation of deep networks. In ICML
Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017 · 2017
Earlier work this paper cites.
Audio set: An ontology and human-labeled dataset for audio events. In ICASSP
Jort F Gemmeke, Daniel PW Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R Channing Moore, Manoj Plakal, and Marvin Ritter. 2017 · 2017
Earlier work this paper cites.
Making the v in vqa matter: Elevating the role of image understanding in visual question answering. In CVPR
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017 · 2017
Earlier work this paper cites.
Zero-Shot Relation Extraction via Reading Comprehension. In CoNLL 2017
Omer Levy, Minjoon Seo, Eunsol Choi, and Luke Zettlemoyer. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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. 2018 · 2018
Earlier work this paper cites.
T-rex: A large scale alignment of natural language with knowledge base triples. In LREC
Hady Elsahar, Pavlos Vougiouklis, Arslen Remaci, Christophe Gravier, Jonathon Hare, Frederique Laforest, and Elena Simperl. 2018 · 2018
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
Earlier work this paper cites.
Commonsenseqa: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2018 · 2018
Earlier work this paper cites.
FEVER: a Large-scale Dataset for Fact Extraction and VERification. In ACL
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018 · 2018
Earlier work this paper cites.
Joaquin Vanschoren. 2018 · 2018
Earlier work this paper cites.
Bias in bios: A case study of semantic representation bias in a high-stakes setting. In FAccT
Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, and Adam Tauman Kalai. 2019 · 2019
Earlier work this paper cites.
Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019 · 2019
Earlier work this paper cites.
Image captioning: Transforming objects into words
Simao Herdade, Armin Kappeler, Kofi Boakye, and Joao Soares. 2019 · 2019
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In NAACL
Jacob Devlin Ming-Wei Chang Kenton and Lee Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, et al · 2019
Earlier work this paper cites.
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. 2019b · 2019
Earlier work this paper cites.
Language Models as Knowledge Bases?. In EMNLP-IJCNLP
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
Earlier work this paper cites.
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In EMNLP-IJCNLP
Nils Reimers and Iryna Gurevych. 2019 · 2019
Earlier work this paper cites.
Fine-tuning language models from human preferences
Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B Brown, Alec Radford, Dario Amodei, Paul Christiano, and Geoffrey Irving. 2019 · 2019
Earlier work this paper cites.
Rewriting a deep generative model. In ECCV
David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, and Antonio Torralba. 2020 · 2020
Earlier work this paper cites.
Language models are few-shot learners. In NeurIPS
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.
Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting. In EMNLP
Sanyuan Chen, Yutai Hou, Yiming Cui, Wanxiang Che, Ting Liu, and Xiangzhan Yu. 2020 · 2020
Earlier work this paper cites.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2020 · 2020
Earlier work this paper cites.
More than a feeling: Benchmarks for sentiment analysis accuracy
Mark Heitmann. 2020 · 2020
Earlier work this paper cites.
How can we know what language models know?
Zhengbao Jiang, Frank F Xu, Jun Araki, and Graham Neubig. 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.
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts. In EMNLP
Taylor Shin, Yasaman Razeghi, Robert L Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2020
Earlier work this paper cites.
Editable Neural Networks. In ICLR
Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry Pyrkin, Sergei Popov, and Artem Babenko. 2020 · 2020
Earlier work this paper cites.
Neural machine translation: A review
Felix Stahlberg. 2020 · 2020
Earlier work this paper cites.
K-adapter: Infusing knowledge into pre-trained models with adapters
Ruize Wang, Duyu Tang, Nan Duan, Zhongyu Wei, Xuanjing Huang, Guihong Cao, Daxin Jiang, Ming Zhou, et al · 2020
Earlier work this paper cites.
A comprehensive survey on transfer learning
Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, and Qing He. 2020 · 2020
Earlier work this paper cites.
Persistent anti-muslim bias in large language models. In AAAI
Abubakar Abid, Maheen Farooqi, and James Zou. 2021 · 2021
Earlier work this paper cites.
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning. In ACL
Armen Aghajanyan, Sonal Gupta, and Luke Zettlemoyer. 2021 · 2021
Earlier work this paper cites.
Editing Factual Knowledge in Language Models. In EMNLP
Nicola De Cao, Wilker Aziz, and Ivan Titov. 2021 · 2021
Earlier work this paper cites.
Measuring and improving consistency in pretrained language models
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard Hovy, Hinrich Schütze, and Yoav Goldberg. 2021 · 2021
Earlier work this paper cites.
Enriching contextualized language model from knowledge graph for biomedical information extraction
Hao Fei, Yafeng Ren, Yue Zhang, Donghong Ji, and Xiaohui Liang. 2021 · 2021
Earlier work this paper cites.
Transformer Feed-Forward Layers Are Key-Value Memories. In EMNLP
Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy. 2021 · 2021
Earlier work this paper cites.
Meta-learning in neural networks: A survey
Timothy Hospedales, Antreas Antoniou, Paul Micaelli, and Amos Storkey. 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
Earlier work this paper cites.
A survey of deep meta-learning
Mike Huisman, Jan N Van Rijn, and Aske Plaat. 2021 · 2021
Earlier work this paper cites.
distilgpt2-finetuned-wikitext2
Yuxuan Ma. 2021 · 2021
Earlier work this paper cites.
Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matrices
Hariom A. Pandya and Brijesh S. Bhatt. 2021 · 2021
Earlier work this paper cites.
KILT: a Benchmark for Knowledge Intensive Language Tasks. In ACL
Fabio Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Nicola De Cao, James Thorne, Yacine Jernite, Vladimir Karpukhin, Jean Maillard, Vassilis Plachouras, Tim Rocktäschel, and Sebastian Riedel. 2021 · 2021
Earlier work this paper cites.
Recipes for Building an Open-Domain Chatbot. In EACL
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Eric Michael Smith, Y-Lan Boureau, et al · 2021
Earlier work this paper cites.
Editing a classifier by rewriting its prediction rules. In NeurIPS
Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, and Aleksander Madry. 2021 · 2021
Cited alongside, same era.
LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs. In NeurIPS Workshop Datacentric AI
Christoph Schuhmann, Robert Kaczmarczyk, Aran Komatsuzaki, Aarush Katta, Richard Vencu, Romain Beaumont, Jenia Jitsev, Theo Coombes, and Clayton Mullis. 2021 · 2021
Cited alongside, same era.
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence. In NAACL
Tal Schuster, Adam Fisch, and Regina Barzilay. 2021 · 2021
Cited alongside, same era.
An exploratory study of COVID-19 misinformation on Twitter
Gautam Kishore Shahi, Anne Dirkson, and Tim A Majchrzak. 2021 · 2021
Cited alongside, same era.
Finetuned Language Models are Zero-Shot Learners
Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le. 2021 · 2021
Cited alongside, same era.
Transformer-Patcher: One Mistake Worth One Neuron. In ICLR
Zeyu Huang, Yikang Shen, Xiaofeng Zhang, Jie Zhou, Wenge Rong, and Zhang Xiong. 2023 · 2023
Closest in time.
Editing models with task arithmetic. In ICLR
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi. 2023 · 2023
Closest in time.
In conversation with Artificial Intelligence: aligning language models with human values
Atoosa Kasirzadeh and Iason Gabriel. 2023 · 2023
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ChatGPT for good? On opportunities and challenges of large language models for education
Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan Günnemann, Eyke Hüllermeier, et al · 2023
Closest in time.
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SituatedQA: Incorporating Extra-Linguistic Contexts into QA. In EMNLP
Michael Zhang and Eunsol Choi. 2021 · 2021
Cited alongside, same era.
FRUIT: Faithfully Reflecting Updated Information in Text. In NAACL
Robert L. Logan IV au2, Alexandre Passos, Sameer Singh, and Ming-Wei Chang. 2022 · 2022
Cited alongside, same era.
Fine-tuning language models to find agreement among humans with diverse preferences. In NeurIPS
Michiel Bakker, Martin Chadwick, Hannah Sheahan, Michael Tessler, Lucy Campbell-Gillingham, Jan Balaguer, Nat McAleese, Amelia Glaese, John Aslanides, Matt Botvinick, et al · 2022
Cited alongside, same era.
FairLex: A Multilingual Benchmark for Evaluating Fairness in Legal Text Processing. In ACL
Ilias Chalkidis, Tommaso Pasini, Sheng Zhang, Letizia Tomada, Sebastian Schwemer, and Anders Søgaard. 2022 · 2022
Cited alongside, same era.
Part of speech tagging: a systematic review of deep learning and machine learning approaches
Alebachew Chiche and Betselot Yitagesu. 2022 · 2022
Cited alongside, same era.
Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al · 2022
Cited alongside, same era.
Knowledge Neurons in Pretrained Transformers. In ACL
Damai Dai, Li Dong, Yaru Hao, Zhifang Sui, Baobao Chang, and Furu Wei. 2022 · 2022
Cited alongside, same era.
Finding supporting examples for in-context learning
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Yasumasa Onoe, Michael J. Q. Zhang, Shankar Padmanabhan, Greg Durrett, and Eunsol Choi. 2023 · 2023
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Emptying the Ocean with a Spoon: Should We Edit Models?. In EMNLP
Yuval Pinter and Michael Elhadad. 2023 · 2023
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ConPET: Continual Parameter-Efficient Tuning for Large Language Models
Chenyang Song, Xu Han, Zheni Zeng, Kuai Li, Chen Chen, Zhiyuan Liu, Maosong Sun, and Tao Yang. 2023a · 2023
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Preference Ranking Optimization for Human Alignment
Feifan Song, Bowen Yu, Minghao Li, Haiyang Yu, Fei Huang, Yongbin Li, and Houfeng Wang. 2023b · 2023
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Stanford Alpaca: An Instruction-following LLaMA model
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Large language models in medicine
Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel Shu Wei Ting. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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Large language models are not fair evaluators
Peiyi Wang, Lei Li, Liang Chen, Dawei Zhu, Binghuai Lin, Yunbo Cao, Qi Liu, Tianyu Liu, and Zhifang Sui. 2023b · 2023
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EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models
Peng Wang, Ningyu Zhang, Xin Xie, Yunzhi Yao, Bozhong Tian, Mengru Wang, Zekun Xi, Siyuan Cheng, Kangwei Liu, Guozhou Zheng, et al · 2023
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Retrieval-augmented multilingual knowledge editing
Weixuan Wang, Barry Haddow, and Alexandra Birch. 2023a · 2023
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Aligning large language models with human: A survey
Yufei Wang, Wanjun Zhong, Liangyou Li, Fei Mi, Xingshan Zeng, Wenyong Huang, Lifeng Shang, Xin Jiang, and Qun Liu. 2023d · 2023
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Xinwei Wu, Junzhuo Li, Minghui Xu, Weilong Dong, Shuangzhi Wu, Chao Bian, and Deyi Xiong. 2023 · 2023
Closest in time.
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Yunzhi Yao, Peng Wang, Bozhong Tian, Siyuan Cheng, Zhoubo Li, Shumin Deng, Huajun Chen, and Ningyu Zhang. 2023 · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
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Siyuan Cheng, Ningyu Zhang, Bozhong Tian, Zelin Dai, Feiyu Xiong, Wei Guo, and Huajun Chen. 2024 · 2024
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Lang Yu, Qin Chen, Jie Zhou, and Liang He. 2024 · 2024
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A comprehensive study of knowledge editing for large language models
Ningyu Zhang, Yunzhi Yao, Bozhong Tian, Peng Wang, Shumin Deng, Mengru Wang, Zekun Xi, Shengyu Mao, Jintian Zhang, Yuansheng Ni, et al · 2024
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