@inproceedings{aguirre-celis-miikkulainen-2020-characterizing,
title = "Characterizing Dynamic Word Meaning Representations in the Brain",
author = "Aguirre-Celis, Nora and
Miikkulainen, Risto",
editor = "Zock, Michael and
Chersoni, Emmanuele and
Lenci, Alessandro and
Santus, Enrico",
booktitle = "Proceedings of the Workshop on the Cognitive Aspects of the Lexicon",
month = dec,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.cogalex-1.15",
pages = "117--128",
abstract = "During sentence comprehension, humans adjust word meanings according to the combination of the concepts that occur in the sentence. This paper presents a neural network model called CEREBRA (Context-dEpendent meaning REpresentation in the BRAin) that demonstrates this process based on fMRI sentence patterns and the Concept Attribute Rep-resentation (CAR) theory. In several experiments, CEREBRA is used to quantify conceptual combination effect and demonstrate that it matters to humans. Such context-based representations could be used in future natural language processing systems allowing them to mirror human performance more accurately.",
}
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%0 Conference Proceedings
%T Characterizing Dynamic Word Meaning Representations in the Brain
%A Aguirre-Celis, Nora
%A Miikkulainen, Risto
%Y Zock, Michael
%Y Chersoni, Emmanuele
%Y Lenci, Alessandro
%Y Santus, Enrico
%S Proceedings of the Workshop on the Cognitive Aspects of the Lexicon
%D 2020
%8 December
%I Association for Computational Linguistics
%C Online
%F aguirre-celis-miikkulainen-2020-characterizing
%X During sentence comprehension, humans adjust word meanings according to the combination of the concepts that occur in the sentence. This paper presents a neural network model called CEREBRA (Context-dEpendent meaning REpresentation in the BRAin) that demonstrates this process based on fMRI sentence patterns and the Concept Attribute Rep-resentation (CAR) theory. In several experiments, CEREBRA is used to quantify conceptual combination effect and demonstrate that it matters to humans. Such context-based representations could be used in future natural language processing systems allowing them to mirror human performance more accurately.
%U https://aclanthology.org/2020.cogalex-1.15
%P 117-128
Markdown (Informal)
[Characterizing Dynamic Word Meaning Representations in the Brain](https://aclanthology.org/2020.cogalex-1.15) (Aguirre-Celis & Miikkulainen, CogALex 2020)
ACL