Search: semantic space — Academic Articles

The fluency-based semantic network of LLMs differs from humans

Ye Wang, Yaling Deng, Ge Wang, Tong Li et al. • Computers in Human Behavior: Artificial Humans (2025)

Modern Large Language Models (LLMs) exhibit complexity and granularity similar to humans in the field of natural language processing, challenging the boundaries between humans and machines in language understanding and creativity. However, ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.chbah.2024.100103

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Computer vision vs. human vision

Bo Zhang • IEEE International Conference on Cognitive Informatics (2010)

In object recognition (classification), it was known that the human brain processes visual information in semantic space mainly, that is, extracting the semantically meaningful features such as line-segments, boundaries, shape and so on. Bu...

OPENALEX DOI: https://doi.org/10.1109/coginf.2010.5599750

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Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat?

Hao Xu, Yuntian Chen, Dongxiao Zhang • Advanced Science (2022)

Abstract The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the “black box” model. Fundamental limitations remain, however, that impede the pac...

DOAJ Open Access (DOAJ) DOI: 10.1002/advs.202204723

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Academic Articles & Research Papers

The fluency-based semantic network of LLMs differs from humans

Computer vision vs. human vision

Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat?