Omni-Attribute is a new open-vocabulary image attribute encoder trained on semantically linked pairs with dual objectives to produce disentangled representations for personalization and compositional generation.
Denoising diffu- sion probabilistic models
4 Pith papers cite this work. Polarity classification is still indexing.
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AIA loss teaches unified multimodal models task-specific cross-modal attention patterns to reduce conflicts between image understanding and generation without architecture decoupling.
OMEGA guides diffusion sampling with per-step constrained optimization and game-theoretic adversarial modeling to generate physically valid and interactive driving scenes, raising valid scene ratios from 32% to 72% and producing 5x more near-collisions.
TES applies early global alignment then iterative CLIP-guided refinement to text embeddings in Stable Diffusion to mitigate bias while preserving quality.
citing papers explorer
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Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization
Omni-Attribute is a new open-vocabulary image attribute encoder trained on semantically linked pairs with dual objectives to produce disentangled representations for personalization and compositional generation.
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AIA: Rethinking Architecture Decoupling Strategy In Unified Multimodal Model
AIA loss teaches unified multimodal models task-specific cross-modal attention patterns to reduce conflicts between image understanding and generation without architecture decoupling.
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Optimization-Guided Diffusion for Interactive Scene Generation
OMEGA guides diffusion sampling with per-step constrained optimization and game-theoretic adversarial modeling to generate physically valid and interactive driving scenes, raising valid scene ratios from 32% to 72% and producing 5x more near-collisions.
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Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization
TES applies early global alignment then iterative CLIP-guided refinement to text embeddings in Stable Diffusion to mitigate bias while preserving quality.