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Towards a universal language of concepts: A survey

2026-09-03 22:37:04
Aishni Parab
arXiv_AI
           
Abstract

Humans can learn and generalize novel concepts from sparse data because they express knowledge in rich structural formats. In this paper, we propose that programs are a strong candidate for universal representation of concepts. We review computational models of concept learning that use programs as their concept representation and evaluate their contribution toward a universal representational language.

Abstract (translated)

URL

https://arxiv.org/abs/2609.04528

PDF

https://arxiv.org/pdf/2609.04528.pdf

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