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Representations from transformer-based unidirectional language models are known to be effective at predicting brain responses to natural language.
The cvxopt linear and quadratic cone program solvers
Lieven Vandenberghe · 2010
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Reconstructing visual experiences from brain activity evoked by natural movies
Shinji Nishimoto, An T Vu, Thomas Naselaris, Yuval Benjamini, Bin Yu, and Jack L Gallant · 2011
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Encoding and decoding in fmri
Thomas Naselaris, Kendrick N Kay, Shinji Nishimoto, and Jack L Gallant · 2011
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Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses
Leila Wehbe, Brian Murphy, Partha Talukdar, Alona Fyshe, Aaditya Ramdas, and Tom Mitchell · 2014
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Converging evidence for the neuroanatomic basis of combinatorial semantics in the angular gyrus
Amy R Price, Michael F Bonner, Jonathan E Peelle, and Murray Grossman · 2015
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Natural speech reveals the semantic maps that tile human cerebral cortex
Alexander G Huth, Wendy A De Heer, Thomas L Griffiths, Frédéric E Theunissen, and Jack L Gallant · 2016
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Measuring the performance of neural models
Oliver Schoppe, Nicol S Harper, Ben DB Willmore, Andrew J King, and Jan WH Schnupp · 2016
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Higher language ability is related to angular gyrus activation increase during semantic processing, independent of sentence incongruency
Helene Van Ettinger-Veenstra, Anita McAllister, Peter Lundberg, Thomas Karlsson, and Maria Engström · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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The hierarchical cortical organization of human speech processing
Wendy A de Heer, Alexander G Huth, Thomas L Griffiths, Jack L Gallant, and Frédéric E Theunissen · 2017
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Incorporating context into language encoding models for fmri
Shailee Jain and Alexander Huth · 2018
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A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy
Alexander JE Kell, Daniel LK Yamins, Erica N Shook, Sam V Norman-Haignere, and Josh H McDermott · 2018
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Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)
Mariya Toneva and Leila Wehbe · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2019
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Bold5000, a public fmri dataset while viewing 5000 visual images
Nadine Chang, John A Pyles, Austin Marcus, Abhinav Gupta, Michael J Tarr, and Elissa M Aminoff · 2019
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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
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 2020
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Artificial neural networks accurately predict language processing in the brain
Martin Schrimpf, Idan Blank, Greta Tuckute, Carina Kauf, Eghbal A. Hosseini, Nancy Kanwisher, Joshua Tenenbaum, and Evelina Fedorenko · 2020
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A survey on contextual embeddings
Qi Liu, Matt J Kusner, and Phil Blunsom · 2020
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wav2vec 2.0: A framework for self-supervised learning of speech representations
Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli · 2020
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The neural architecture of language: Integrative modeling converges on predictive processing
Martin Schrimpf, Idan Asher Blank, Greta Tuckute, Carina Kauf, Eghbal A Hosseini, Nancy Kanwisher, Joshua B Tenenbaum, and Evelina Fedorenko · 2021
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Voxelwise encoding models show that cerebellar language representations are highly conceptual
Amanda LeBel, Shailee Jain, and Alexander G. Huth · 2021
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Low-dimensional structure in the space of language representations is reflected in brain responses
Richard Antonello, Javier S Turek, Vy Vo, and Alexander Huth · 2021
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Inductive biases, pretraining and fine-tuning jointly account for brain responses to speech
Juliette Millet and Jean-Remi King · 2021
Decoding speech from non-invasive brain recordings
Alexandre Défossez, Charlotte Caucheteux, Jérémy Rapin, Ori Kabeli, and Jean-Rémi King · 2022
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Dissecting neural computations of the human auditory pathway using deep neural networks for speech
Yuanning Li, Gopala K Anumanchipalli, Abdelrahman Mohamed, Junfeng Lu, Jinsong Wu, and Edward F Chang · 2022
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Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al · 2022
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Wavlm: Large-scale self-supervised pre-training for full stack speech processing
Sanyuan Chen, Chengyi Wang, Zhengyang Chen, Yu Wu, Shujie Liu, Zhuo Chen, Jinyu Li, Naoyuki Kanda, Takuya Yoshioka, Xiong Xiao, et al · 2022
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Hubert: Self-supervised speech representation learning by masked prediction of hidden units
Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed · 2021
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Superb: Speech processing universal performance benchmark
Shu-wen Yang, Po-Han Chi, Yung-Sung Chuang, Cheng-I Jeff Lai, Kushal Lakhotia, Yist Y Lin, Andy T Liu, Jiatong Shi, Xuankai Chang, Guan-Ting Lin, et al · 2021
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The left angular gyrus is causally involved in context-dependent integration and associative encoding during narrative reading
Francesca M Branzi, Gorana Pobric, JeYoung Jung, and Matthew A Lambon Ralph · 2021
Cited alongside, same era.
The “narratives” fmri dataset for evaluating models of naturalistic language comprehension
Samuel A Nastase, Yun-Fei Liu, Hanna Hillman, Asieh Zadbood, Liat Hasenfratz, Neggin Keshavarzian, Janice Chen, Christopher J Honey, Yaara Yeshurun, Mor Regev, et al · 2021
Cited alongside, same era.
Competition-level code generation with alphacode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, et al · 2022
Cited alongside, same era.
Deep language algorithms predict semantic comprehension from brain activity
Charlotte Caucheteux, Alexandre Gramfort, and Jean-Rémi King · 2022
Cited alongside, same era.
Shared computational principles for language processing in humans and deep language models
Ariel Goldstein, Zaid Zada, Eliav Buchnik, Mariano Schain, Amy Price, Bobbi Aubrey, Samuel A Nastase, Amir Feder, Dotan Emanuel, Alon Cohen, et al · 2022
Cited alongside, same era.
Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, and Ilya Sutskever · 2022
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A natural language fmri dataset for voxelwise encoding models
Amanda LeBel, Lauren Wagner, Shailee Jain, Aneesh Adhikari-Desai, Bhavin Gupta, Allyson Morgenthal, Jerry Tang, Lixiang Xu, and Alexander G Huth · 2022
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Predictive coding or just feature discovery? an alternative account of why language models fit brain data
Richard Antonello and Alexander Huth · 2022
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A massive 7t fmri dataset to bridge cognitive neuroscience and artificial intelligence
Emily J Allen, Ghislain St-Yves, Yihan Wu, Jesse L Breedlove, Jacob S Prince, Logan T Dowdle, Matthias Nau, Brad Caron, Franco Pestilli, Ian Charest, et al · 2022
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Large language models are zero-shot reasoners, 2023
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2023
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Are emergent abilities of large language models a mirage?, 2023
Rylan Schaeffer, Brando Miranda, and Sanmi Koyejo · 2023
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Training language models to summarize narratives improves brain alignment, 2023
Khai Loong Aw and Mariya Toneva · 2023
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The cortical representation of language timescales is shared between reading and listening
Catherine Chen, Tom Dupré la Tour, Jack Gallant, Daniel Klein, and Fatma Deniz · 2023
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Computational Language Modeling and the Promise of in Silico Experimentation
Shailee Jain, Vy A. Vo, Leila Wehbe, and Alexander G. Huth · 2023
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Evidence of a predictive coding hierarchy in the human brain listening to speech
Charlotte Caucheteux, Alexandre Gramfort, and Jean-Rémi King · 2023
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Using artificial neural networks to ask ‘why’questions of minds and brains
Nancy Kanwisher, Meenakshi Khosla, and Katharina Dobs · 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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Semantic reconstruction of continuous language from non-invasive brain recordings
Jerry Tang, Amanda LeBel, Shailee Jain, and Alexander G Huth · 2023
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Stacked regressions and structured variance partitioning for interpretable brain maps
Ruogu Lin, Thomas Naselaris, Kendrick Kay, and Leila Wehbe · 2023
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Driving and suppressing the human language network using large language models
Greta Tuckute, Aalok Sathe, Shashank Srikant, Maya Taliaferro, Mingye Wang, Martin Schrimpf, Kendrick Kay, and Evelina Fedorenko · 2023
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