main webpage W Topic Generative Grammar arXiv (Cornell University) Concept-Centric Token Interpretation for Vector-Quantized Generative Models 2025 Vector-Quantized Generative Models (VQGMs) have emerged as powerful tools for image generation. However, the key component of VQGMs -- the codebook of discrete tokens -- is still not well understood, e.g., which tokens are critical to generate an image of a c… Article Open Generative Grammar Open Article Page

Generative Grammar

Theory in linguistics Generative grammar , or generativism , is a linguistic theory that regards linguistics as the study of a hypothesised innate grammatical structure. It is a biological or biologistic modification of earlier structuralist theories of linguistics, deriving from logical syntax and glossematics. Generative grammar considers grammar as a system of rules that generates exactly those combinations of words that form grammatical sentences in a given language. It is a system of explicit rules that may apply repeatedly to generate an indefinite number of sentences which can be as long as one wants them to be. The difference from structural and functional models is that the object is base-generated within the verb phrase in generative grammar. Critical Symbolic Virtual Narrative Open Generative Grammar Open Article Page

Exploring foci of: arXiv (Cornell University) Concept-Centric Token Interpretation for Vector-Quantized Generative Models 2025 Vector-Quantized Generative Models (VQGMs) have emerged as powerful tools for image generation. However, the key component of VQGMs -- the codebook of discrete tokens -- is still not well understood, e.g., which tokens are critical to generate an image of a certain concept? This paper introduces Concept-Oriented Token Explanation (CORTEX), a novel approach for interpreting VQGMs by identifying concept-specific token combinations. Our framework employs two methods: (1) a sample-level explanation method that analyze… Open Article Page

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Explore Generative Grammar W Topic Generative Grammar arXiv (Cornell University) Concept-Centric Token Interpretation for Vector-Quantized Generative Models 2025 Vector-Quantized Generative Models (VQGMs) have emerged as powerful tools for image generation. However, the key component of VQGMs -- the codebook of discrete tokens -- is still not well understood, e.g., which tokens are critical to generate an image of a c… Article Critical Symbolic Virtual Narrative Open Generative Grammar Open Article Page