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    <abstract>How do people understand the meaning of the word “small” when used to describe a mosquito, a church, or a planet? While humans have a remarkable ability to form meanings by combining existing concepts, modeling this process is challenging. This paper addresses that challenge through CEREBRA (Context-dEpendent meaning REpresentations in the BRAin) neural network model. CEREBRA characterizes how word meanings dynamically adapt in the context of a sentence by decomposing sentence fMRI into words and words into embodied brain-based semantic features. It demonstrates that words in different contexts have different representations and the word meaning changes in a way that is meaningful to human subjects. CEREBRA’s context-based representations can potentially be used to make NLP applications more human-like.</abstract>
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%0 Conference Proceedings
%T Understanding the Semantic Space: How Word Meanings Dynamically Adapt in the Context of a Sentence
%A Aguirre-Celis, Nora
%A Miikkulainen, Risto
%S Proceedings of the 2021 Workshop on Semantic Spaces at the Intersection of NLP, Physics, and Cognitive Science (SemSpace)
%D 2021
%8 June
%I Association for Computational Linguistics
%C Groningen, The Netherlands
%F aguirre-celis-miikkulainen-2021-understanding
%X How do people understand the meaning of the word “small” when used to describe a mosquito, a church, or a planet? While humans have a remarkable ability to form meanings by combining existing concepts, modeling this process is challenging. This paper addresses that challenge through CEREBRA (Context-dEpendent meaning REpresentations in the BRAin) neural network model. CEREBRA characterizes how word meanings dynamically adapt in the context of a sentence by decomposing sentence fMRI into words and words into embodied brain-based semantic features. It demonstrates that words in different contexts have different representations and the word meaning changes in a way that is meaningful to human subjects. CEREBRA’s context-based representations can potentially be used to make NLP applications more human-like.
%U https://aclanthology.org/2021.semspace-1.1
%P 1-11

Markdown (Informal)

[Understanding the Semantic Space: How Word Meanings Dynamically Adapt in the Context of a Sentence](https://aclanthology.org/2021.semspace-1.1) (Aguirre-Celis & Miikkulainen, SemSpace 2021)

• Understanding the Semantic Space: How Word Meanings Dynamically Adapt in the Context of a Sentence (Aguirre-Celis & Miikkulainen, SemSpace 2021)

ACL

• Nora Aguirre-Celis and Risto Miikkulainen. 2021. Understanding the Semantic Space: How Word Meanings Dynamically Adapt in the Context of a Sentence. In Proceedings of the 2021 Workshop on Semantic Spaces at the Intersection of NLP, Physics, and Cognitive Science (SemSpace), pages 1–11, Groningen, The Netherlands. Association for Computational Linguistics.