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Large Language Models (LLMs) are being used for a wide variety of tasks.
Computational analysis of present-day american english
W. Nelson Francis and Henry Kucera · 1967
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Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition
Y. C. Pati, Ramin Rezaiifar, and P. S. Krishnaprasad · 1993
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Natural language processing with python: analyzing text with the natural language toolkit
Steven Bird, Ewan Klein, and Edward Loper · 2009
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Sparse and redundant representations: from theory to applications in signal and image processing
Michael Elad · 2010
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Orthogonal matching pursuit for sparse signal recovery with noise
T. Tony Cai and Lie Wang · 2011
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Block-sparse recovery via convex optimization
Ehsan Elhamifar and René Vidal · 2012
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Efficient Estimation of Word Representations in Vector Space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Distributed Representations of Words and Phrases and their Compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Linguistic Regularities in Continuous Space Word Representations
Tomas Mikolov, Wen-tau Yih, and Geoffrey Zweig · 2013
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Linguistic Regularities in Sparse and Explicit Word Representations
Omer Levy and Yoav Goldberg · 2014
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Glove: Global Vectors for Word Representation
Jeffrey Pennington, Richard Socher, and Christopher Manning · 2014
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Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai · 2016
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Learning deep parsimonious representations
Renjie Liao, Alex Schwing, Richard Zemel, and Raquel Urtasun · 2016
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Swivel: Improving Embeddings by Noticing What’s Missing
Noam Shazeer, Ryan Doherty, Colin Evans, and Chris Waterson · 2016
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Generalized Principal Component Analysis
René Vidal, Yi Ma, and Shankar Sastry · 2016
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Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering
Chong You, Chun Guang Li, Daniel P Robinson, and Rene Vidal · 2016
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Skip-Gram - Zipf + Uniform = Vector Additivity
Alex Gittens, Dimitris Achlioptas, and Michael W. Mahoney · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Linear Algebraic Structure of Word Senses, with Applications to Polysemy
Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, and Andrej Risteski · 2018
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Ole: Orthogonal low-rank embedding-a plug and play geometric loss for deep learning
José Lezama, Qiang Qiu, Pablo Musé, and Guillermo Sapiro · 2018
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Analogies Explained: Towards Understanding Word Embeddings
Carl Allen and Timothy Hospedales · 2019
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A Latent Variable Model Approach to PMI-based Word Embeddings
Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, and Andrej Risteski · 2019
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Towards Understanding Linear Word Analogies
Kawin Ethayarajh, David Duvenaud, and Graeme Hirst · 2019
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Billion-scale similarity search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou · 2019
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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela · 2020
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Umap: Uniform manifold approximation and projection for dimension reduction
Leland McInnes, John Healy, and James Melville · 2020
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Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave · 2021
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Self-conditioning pre-trained language models
Xavier Suau Cuadros, Luca Zappella, and Nicholas Apostoloff · 2022
Cited alongside, same era.
Nelson Elhage, Tristan Hume, Catherine Olsson, Nicholas Schiefer, Tom Henighan, Shauna Kravec, Zac Hatfield-Dodds, Robert Lasenby, Dawn Drain, Carol Chen, Roger Grosse, Sam McCandlish, Jared Kaplan, Dario Amodei, Martin Wattenberg, and Christopher Olah · 2022
Cited alongside, same era.
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 · 2022
Cited alongside, same era.
Revisiting Additive Compositionality: AND, OR and NOT Operations with Word Embeddings
Masahiro Naito, Sho Yokoi, Geewook Kim, and Hidetoshi Shimodaira · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Emergent Linear Representations in World Models of Self-Supervised Sequence Models
Neel Nanda, Andrew Lee, and Martin Wattenberg · 2023
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OpenAI · 2023
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Logic-lm: Empowering large language models with symbolic solvers for faithful logical reasoning
Liangming Pan, Alon Albalak, Xinyi Wang, and William Yang Wang · 2023
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The Linear Representation Hypothesis and the Geometry of Large Language Models
Kiho Park, Yo Joong Choe, and Victor Veitch · 2023
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Replug: Retrieval-augmented black-box language models
Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, and Wen tau Yih · 2023
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Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 2022
Cited alongside, same era.
“I’m sorry to hear that”: Finding new biases in language models with a holistic descriptor dataset
Eric Michael Smith, Melissa Hall, Melanie Kambadur, Eleonora Presani, and Adina Williams · 2022
Cited alongside, same era.
Extracting Latent Steering Vectors from Pretrained Language Models
Nishant Subramani, Nivedita Suresh, and Matthew Peters · 2022
Cited alongside, same era.
Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus · 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 Chi, Quoc Le, and Denny Zhou · 2022
Cited alongside, same era.
High-dimensional data analysis with low-dimensional models: Principles, computation, and applications
John Wright and Yi Ma · 2022
Cited alongside, same era.
InstructBLIP: Towards general-purpose vision-language models with instruction tuning
Wenliang Dai, Junnan Li, Dongxu Li, Anthony Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, and Steven Hoi · 2023
Cited alongside, same era.
Rephrase and respond: Let large language models ask better questions for themselves
Yihe Deng, Weitong Zhang, Zixiang Chen, and Quanquan Gu · 2023
Cited alongside, same era.
Linear Representations of Sentiment in Large Language Models
Curt Tigges, Oskar John Hollinsworth, Atticus Geiger, and Neel Nanda · 2023
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Linear spaces of meanings: compositional structures in vision-language models
Matthew Trager, Pramuditha Perera, Luca Zancato, Alessandro Achille, Parminder Bhatia, and Stefano Soatto · 2023
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Activation addition: Steering language models without optimization
Alexander Matt Turner, Lisa Thiergart, David Udell, Gavin Leech, Ulisse Mini, and Monte MacDiarmid · 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 · 2023
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Concept algebra for (score-based) text-controlled generative models
Zihao Wang, Lin Gui, Jeffrey Negrea, and Victor Veitch · 2023
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Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao, and Karthik Narasimhan · 2023
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Zeyu Yun, Yubei Chen, Bruno A Olshausen, and Yann LeCun · 2023
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Almanac: Retrieval-augmented language models for clinical medicine
Cyril Zakka, Akash Chaurasia, Rohan Shad, Alex R. Dalal, Jennifer L. Kim, Michael Moor, Kevin Alexander, Euan Ashley, Jack Boyd, Kathleen Boyd, Karen Hirsch, Curt Langlotz, Joanna Nelson, and William Hiesinger · 2023
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Controllable text-to-image generation with gpt-4
Tianjun Zhang, Yi Zhang, Vibhav Vineet, Neel Joshi, and Xin Wang · 2023
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Siren’s song in the ai ocean: A survey on hallucination in large language models
Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, Longyue Wang, Anh Tuan Luu, Wei Bi, Freda Shi, and Shuming Shi · 2023
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Representation engineering: A top-down approach to ai transparency
Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, Shashwat Goel, Nathaniel Li, Michael J. Byun, Zifan Wang, Alex Mallen, Steven Basart, Sanmi Koyejo, Dawn Song, Matt Fredrikson, Zico Kolter, and Dan Hendrycks · 2023
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Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J. Zico Kolter, and Matt Fredrikson · 2023
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Discovering Latent Knowledge in Language Models Without Supervision
Collin Burns, Haotian Ye, Dan Klein, and Jacob Steinhardt · 2024
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The efficiency spectrum of large language models: An algorithmic survey
Tianyu Ding, Tianyi Chen, Haidong Zhu, Jiachen Jiang, Yiqi Zhong, Jinxin Zhou, Guangzhi Wang, Zhihui Zhu, Ilya Zharkov, and Luming Liang · 2024
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Finding alignments between interpretable causal variables and distributed neural representations
Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, and Noah Goodman · 2024
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Query-based adversarial prompt generation
Jonathan Hayase, Ema Borevkovic, Nicholas Carlini, Florian Tramèr, and Milad Nasr · 2024
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Ai alignment: A comprehensive survey
Jiaming Ji, Tianyi Qiu, Boyuan Chen, Borong Zhang, Hantao Lou, Kaile Wang, Yawen Duan, Zhonghao He, Jiayi Zhou, Zhaowei Zhang, Fanzhi Zeng, Kwan Yee Ng, Juntao Dai, Xuehai Pan, Aidan O’Gara, Yingshan Lei, Hua Xu, Brian Tse, Jie Fu, Stephen McAleer, Yaodong Yang, Yizhou Wang, Song-Chun Zhu, Yike Guo, and Wen Gao · 2024
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On the Origins of Linear Representations in Large Language Models
Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam, and Victor Veitch · 2024
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Long-context llms struggle with long in-context learning
Tianle Li, Ge Zhang, Quy Duc Do, Xiang Yue, and Wenhu Chen · 2024
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A systematic survey of prompt engineering in large language models: Techniques and applications
Pranab Sahoo, Ayush Kumar Singh, Sriparna Saha, Vinija Jain, Samrat Mondal, and Aman Chadha · 2024
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Function vectors in large language models
Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, and David Bau · 2024
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Detoxifying large language models via knowledge editing
Mengru Wang, Ningyu Zhang, Ziwen Xu, Zekun Xi, Shumin Deng, Yunzhi Yao, Qishen Zhang, Linyi Yang, Jindong Wang, and Huajun Chen · 2024
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Large language models as optimizers
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, and Xinyun Chen · 2024
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White-box transformers via sparse rate reduction
Yaodong Yu, Sam Buchanan, Druv Pai, Tianzhe Chu, Ziyang Wu, Shengbang Tong, Benjamin Haeffele, and Yi Ma · 2024
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