World Properties without World Models: Recovering Spatial and Temporal Structure from Co-occurrence Statistics in Static Word Embeddings | ScienceToStartup | ScienceToStartup

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References (16)

[1]

Language Models Represent Space and Time

2023Wes Gurnee, Max Tegmark

[2]

Mapping Language Models to Grounded Conceptual Spaces

2022Roma Patel, Ellie Pavlick

[3]

Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color

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"Explore how static word embeddings like GloVe and Word2Vec can recover spatial and temporal data from text co-occurrence."

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World Properties without World Models: Recovering Spatial and Temporal Structure from Co-occurrence Statistics in Static Word Embeddings

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Founder's Pitch

"Explore how static word embeddings like GloVe and Word2Vec can recover spatial and temporal data from text co-occurrence."

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World Properties without World Models: Recovering Spatial and Temporal Structure from Co-occurrence Statistics in Static Word Embeddings

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Founder's Pitch

"Explore how static word embeddings like GloVe and Word2Vec can recover spatial and temporal data from text co-occurrence."

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