Fetching the paper…
Reading the bibliography…
Representational Similarity Analysis (RSA) is a technique developed by neuroscientists for comparing activity patterns of different measurement modalities (e.g., fMRI, electrophysiology, behavior).
Correlating neural and symbolic representations of language
Chrupała, G. and Alishahi, A. (2019) · 1905
Earlier work this paper cites.
Bert rediscovers the classical nlp pipeline
Tenney, I., Das, D., and Pavlick, E. (2019) · 1905
Earlier work this paper cites.
A model and an hypothesis for language structure
Yngve, V. H. (1960) · 1909
Earlier work this paper cites.
Second-order isomorphism of internal representations: Shapes of states
Shepard, R. N. and Chipman, S. (1970) · 1970
Earlier work this paper cites.
Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity
Rayner, K. and Duffy, S. A. (1986) · 1986
Earlier work this paper cites.
Lexical ambiguity and fixation times in reading
Duffy, S. A., Morris, R. K., and Rayner, K. (1988) · 1988
Earlier work this paper cites.
100 million words of english: the british national corpus (bnc)
Leech, G. N. (1992) · 1992
Earlier work this paper cites.
Wordnet: a lexical database for english
Miller, G. A. (1995) · 1995
Earlier work this paper cites.
The earth mover’s distance as a metric for image retrieval
Rubner, Y., Tomasi, C., and Guibas, L. (2000) · 2000
Earlier work this paper cites.
The dundee corpus
Kennedy, A., Hill, R., and Pynte, J. (2003) · 2003
Earlier work this paper cites.
Eye movements of highly skilled and average readers: Differential effects of frequency and predictability
Ashby, J., Rayner, K., and Clifton, C. (2005) · 2005
Earlier work this paper cites.
Information-based functional brain mapping
Kriegeskorte, N., Goebel, R., and Bandettini, P. (2006) · 2006
Earlier work this paper cites.
Eye movements: A window on mind and brain
Van Gompel, R. P. (2007) · 2007
Earlier work this paper cites.
Representational similarity analysis-connecting the branches of systems neuroscience
Kriegeskorte, N., Mur, M., and Bandettini, P. A. (2008) · 2008
Cited alongside, same era.
Expectation-based syntactic comprehension
Levy, R. (2008) · 2008
Cited alongside, same era.
With blinkers on: Robust prediction of eye movements across readers
Matthies, F. and Søgaard, A. (2013) · 2013
Cited alongside, same era.
A toolbox for representational similarity analysis
Nili, H., Wingfield, C., Walther, A., Su, L., Marslen-Wilson, W., and Kriegeskorte, N. (2014) · 2014
Cited alongside, same era.
Using eye movements to evaluate the cognitive processes involved in text comprehension
Raney, G. E., Campbell, S. J., and Bovee, J. C. (2014) · 2014
Cited alongside, same era.
Fine-grained analysis of sentence embeddings using auxiliary prediction tasks
Deep rnns encode soft hierarchical syntax
Blevins, T., Levy, O., and Zettlemoyer, L. (2018) · 2018
Later among the works it cites.
How agents see things: On visual representations in an emergent language game
Bouchacourt, D. and Baroni, M. (2018) · 2018
Later among the works it cites.
Evaluating compositionality in sentence embeddings
Dasgupta, I., Guo, D., Stuhlmüller, A., Gershman, S. J., and Goodman, N. D. (2018) · 2018
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. (2018) · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Adi, Y., Kermany, E., Belinkov, Y., Lavi, O., and Goldberg, Y. (2016) · 2016
Cited alongside, same era.
Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence
Cichy, R. M., Khosla, A., Pantazis, D., Torralba, A., and Oliva, A. (2016) · 2016
Cited alongside, same era.
Modeling human reading with neural attention
Hahn, M. and Keller, F. (2016) · 2016
Cited alongside, same era.
Assessing the ability of lstms to learn syntax-sensitive dependencies
Linzen, T., Dupoux, E., and Goldberg, Y. (2016) · 2016
Cited alongside, same era.
Evaluating layers of representation in neural machine translation on part-of-speech and semantic tagging tasks
Belinkov, Y., Màrquez, L., Sajjad, H., Durrani, N., Dalvi, F., and Glass, J. (2017) · 2017
Cited alongside, same era.
Representations of language in a model of visually grounded speech signal
Chrupała, G., Gelderloos, L., and Alishahi, A. (2017) · 2017
Cited alongside, same era.
Hupkes, D., Veldhoen, S., and Zuidema, W. (2017) · 2017
Cited alongside, same era.
Gulordava, K., Bojanowski, P., Grave, E., Linzen, T., and Baroni, M. (2018) · 2018
Later among the works it cites.
Rearranging the familiar: Testing compositional generalization in recurrent networks
Loula, J., Baroni, M., and Lake, B. M. (2018) · 2018
Later among the works it cites.
Targeted syntactic evaluation of language models
Marvin, R. and Linzen, T. (2018) · 2018
Later among the works it cites.
The natural language decathlon: Multitask learning as question answering
McCann, B., Keskar, N. S., Xiong, C., and Socher, R. (2018) · 2018
Later among the works it cites.
Deep contextualized word representations
Peters, M. E., Neumann, M., Iyyer, M., Gardner, M., Clark, C., Lee, K., and Zettlemoyer, L. (2018) · 2018
Later among the works it cites.
What do you learn from context? probing for sentence structure in contextualized word representations
Tenney, I., Xia, P., Chen, B., Wang, A., Poliak, A., McCoy, R. T., Kim, N., Van Durme, B., Bowman, S., Das, D., et al. (2018) · 2018
Later among the works it cites.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Wang, A., Singh, A., Michael, J., Hill, F., Levy, O., and Bowman, S. R. (2018) · 2018
Later among the works it cites.
Blackbox meets blackbox: Representational similarity & stability analysis of neural language models and brains
Abnar, S., Beinborn, L., Choenni, R., and Zuidema, W. (2019) · 2019
Closest in time.