PDF] Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses
Por um escritor misterioso
Last updated 13 abril 2025
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An encoder-decoder transfer learning method from computer vision is adapted to investigate the structure among 100 different feature spaces extracted from hidden representations of various networks trained on language tasks and reveals a low-dimensional structure where language models and translation models smoothly interpolate between word embeddings, syntactic and semantic tasks, and future word embedDings. How related are the representations learned by neural language models, translation models, and language tagging tasks? We answer this question by adapting an encoder-decoder transfer learning method from computer vision to investigate the structure among 100 different feature spaces extracted from hidden representations of various networks trained on language tasks. This method reveals a low-dimensional structure where language models and translation models smoothly interpolate between word embeddings, syntactic and semantic tasks, and future word embeddings. We call this low-dimensional structure a language representation embedding because it encodes the relationships between representations needed to process language for a variety of NLP tasks. We find that this representation embedding can predict how well each individual feature space maps to human brain responses to natural language stimuli recorded using fMRI. Additionally, we find that the principal dimension of this structure can be used to create a metric which highlights the brain's natural language processing hierarchy. This suggests that the embedding captures some part of the brain's natural language representation structure.
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Frontiers The Embodiment of Architectural Experience: A Methodological Perspective on Neuro-Architecture
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Physics-Inspired Structural Representations for Molecules and Materials
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The Brain Basis of Language Processing: From Structure to Function
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Mental Phenomena Don't Map Into the Brain as Expected
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PDF] Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses
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Multicomputation: A Fourth Paradigm for Theoretical Science—Stephen Wolfram Writings
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Sensors, Free Full-Text
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Neural representation of linguistic feature hierarchy reflects second- language proficiency - ScienceDirect
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Frontiers The Margins of the Language Network in the Brain
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