On the Computational Modeling of Meaning: Embodied Cognition Intertwined with Emotion
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Abstract (arXiv)
This document chronicles this author's attempt to explore how words come to mean what they do, with a particular focus on child language acquisition and what that means for models of language understanding.footnoteI say historical because I synthesize the ideas based on when I discovered them and how those ideas influenced my later thinking. I explain the setting for child language learning, how embodiment -- being able to perceive and enact in the world, including knowledge of concrete and abstract concepts -- is crucial, and how emotion and cognition relate to each other and the language learning process. I end with what I think are some of the requirements for a language-learning agent that learns language in a setting similar to that of children. This paper can act as a potential guide for ongoing and future work in modeling language.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 49 references that are in the map. First posted on arXiv 10 Jul 2023.
Builds on
6 of 49 references.
References · 6
- 2017Attention Is All You Needcited by 59,932
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2020Experience Grounds Languagecited by 241
- 2014The Latent Structure of Dictionariescited by 9
- 2023What A Situated Language-Using Agent Must be Able to Do: A Top-Down Analysiscited by 8
- 2023Vision Language Transformers: A Surveycited by 5
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Citing papers per year: 2026: 1.
1 paper.