Fetching the paper…
Reading the bibliography…
Brain decoding, understood as the process of mapping brain activities to the stimuli that generated them, has been an active research area in the last years.
Roberta: A robustly optimized bert pretraining approach
Liu, Y.; Ott, M.; Goyal, N.; Du, J.; Joshi, M.; Chen, D.; Levy, O.; Lewis, M.; Zettlemoyer, L.; and Stoyanov, V. 2019 · 1907
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2019 · 1910
Earlier work this paper cites.
Human brain activity for machine attention
Muttenthaler, L.; Hollenstein, N.; and Barrett, M. 2020 · 2006
Earlier work this paper cites.
Predicting human brain activity associated with the meanings of nouns
Mitchell, T. M.; Shinkareva, S. V.; Carlson, A.; Chang, K.-M.; Malave, V. L.; Mason, R. A.; and Just, M. A. 2008 · 2008
Earlier work this paper cites.
Zero-shot learning with semantic output codes
Palatucci, M.; Pomerleau, D.; Hinton, G. E.; and Mitchell, T. M. 2009 · 2009
Earlier work this paper cites.
A neurosemantic theory of concrete noun representation based on the underlying brain codes
Just, M. A.; Cherkassky, V. L.; Aryal, S.; and Mitchell, T. M. 2010 · 2010
Earlier work this paper cites.
Reconstructing visual experiences from brain activity evoked by natural movies
Nishimoto, S.; Vu, A. T.; Naselaris, T.; Benjamini, Y.; Yu, B.; and Gallant, J. L. 2011 · 2011
Earlier work this paper cites.
Glove: Global vectors for word representation
Pennington, J.; Socher, R.; and Manning, C. D. 2014 · 2014
Earlier work this paper cites.
Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses
Wehbe, L.; Murphy, B.; Talukdar, P.; Fyshe, A.; Ramdas, A.; and Mitchell, T. 2014 · 2014
Earlier work this paper cites.
Facenet: A unified embedding for face recognition and clustering
Schroff, F.; Kalenichenko, D.; and Philbin, J. 2015 · 2015
Earlier work this paper cites.
Xgboost: A scalable tree boosting system
Chen, T.; and Guestrin, C. 2016 · 2016
Cited alongside, same era.
Generation and evaluation of a cortical area parcellation from resting-state correlations
Gordon, E. M.; Laumann, T. O.; Adeyemo, B.; Huckins, J. F.; Kelley, W. M.; and Petersen, S. E. 2016 · 2016
Cited alongside, same era.
How concepts are encoded in the human brain: a modality independent, category-based cortical organization of semantic knowledge
Handjaras, G.; Ricciardi, E.; Leo, A.; Lenci, A.; Cecchetti, L.; Cosottini, M.; Marotta, G.; and Pietrini, P. 2016 · 2016
Cited alongside, same era.
Natural speech reveals the semantic maps that tile human cerebral cortex
Huth, A. G.; De Heer, W. A.; Griffiths, T. L.; Theunissen, F. E.; and Gallant, J. L. 2016 · 2016
Cited alongside, same era.
Speaking, seeing, understanding: Correlating semantic models with conceptual representation in the brain
Bulat, L.; Clark, S.; and Shutova, E. 2017 · 2017
Cited alongside, same era.
Toward a universal decoder of linguistic meaning from brain activation
Pereira, F.; Lou, B.; Pritchett, B.; Ritter, S.; Gershman, S. J.; Kanwisher, N.; Botvinick, M.; and Fedorenko, E. 2018 · 2018
Later among the works it cites.
Modeling semantic encoding in a common neural representational space
Van Uden, C. E.; Nastase, S. A.; Connolly, A. C.; Feilong, M.; Hansen, I.; Gobbini, M. I.; and Haxby, J. V. 2018 · 2018
Later among the works it cites.
Linking artificial and human neural representations of language
Gauthier, J.; and Levy, R. 2019 · 2019
Later among the works it cites.
Reconstructing meaning from bits of information
Kivisaari, S. L.; van Vliet, M.; Hultén, A.; Lindh-Knuutila, T.; Faisal, A.; and Salmelin, R. 2019 · 2019
Later among the works it cites.
Language models are unsupervised multitask learners
Radford, A.; Wu, J.; Child, R.; Luan, D.; Amodei, D.; and Sutskever, I. 2019 · 2019
Later among the works it cites.
Inducing brain-relevant bias in natural language processing models
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Neural discrete representation learning
Van Den Oord, A.; Vinyals, O.; et al. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
Harry-Potter-Book-Text-Generator
Davis, S. W. 2018 · 2018
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
Cited alongside, same era.
Does the brain represent words? An evaluation of brain decoding studies of language understanding
Gauthier, J.; and Ivanova, A. 2018 · 2018
Cited alongside, same era.
Schwartz, D.; Toneva, M.; and Wehbe, L. 2019 · 2019
Later among the works it cites.
Towards sentence-level brain decoding with distributed representations
Sun, J.; Wang, S.; Zhang, J.; and Zong, C. 2019 · 2019
Later among the works it cites.
Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)
Toneva, M.; and Wehbe, L. 2019 · 2019
Later among the works it cites.
Leveraging shared connectivity to aggregate heterogeneous datasets into a common response space
Nastase, S. A.; Liu, Y.-F.; Hillman, H.; Norman, K. A.; and Hasson, U. 2020 · 2020
Closest in time.
Probing Brain Activation Patterns by Dissociating Semantics and Syntax in Sentences
Wang, S.; Zhang, J.; Lin, N.; and Zong, C. 2020 · 2020
Closest in time.