A Note on Semantic Diffusion
By: Alexander P. Ryjov, Alina A. Egorova
Potential Business Impact:
Helps computers design things by improving ideas.
This paper provides an in-depth examination of the concept of semantic diffusion as a complementary instrument to large language models (LLMs) for design applications. Conventional LLMs and diffusion models fail to induce a convergent, iterative refinement process: each invocation of the diffusion mechanism spawns a new stochastic cycle, so successive outputs do not relate to prior ones and convergence toward a desired design is not guaranteed. The proposed hybrid framework - "LLM + semantic diffusion" - resolves this limitation by enforcing an approximately convergent search procedure, thereby formally addressing the problem of localized design refinement.
Similar Papers
Cross-Cultural Fashion Design via Interactive Large Language Models and Diffusion Models
Computation and Language
AI creates diverse fashion designs from text.
Exploring the Deep Fusion of Large Language Models and Diffusion Transformers for Text-to-Image Synthesis
CV and Pattern Recognition
Makes AI create better pictures from words.
Diffuse Thinking: Exploring Diffusion Language Models as Efficient Thought Proposers for Reasoning
Computation and Language
Makes computers think better and faster.