MasqLoRA shows that an independent LoRA adapter can be trained on a few trigger-target pairs to backdoor diffusion models with 99.8% success rate while remaining stealthy when the trigger is absent.
Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
7 Pith papers cite this work. Polarity classification is still indexing.
7
Pith papers citing it
citation-role summary
background 3
citation-polarity summary
fields
cs.CV 7years
2026 7roles
background 3polarities
background 3representative citing papers
AttriStory adds a benchmark and AttriLoss-based latent optimization to improve faithful rendering of fine-grained attributes such as clothing color and texture in diffusion-model visual storytelling.
Fashion130K dataset and UMC framework align text and visual prompts to generate more consistent fashion outfits than prior state-of-the-art methods.
Gate-and-Merge enables zero-shot compositional personalization of VLMs by independently learning concept-specific LoRA adapters and merging them in weight space with cue-based gating to suppress interference.
RealDiffusion uses heat diffusion as a dissipative prior and a region-aware stochastic process inside a training-free physics-informed attention mechanism to improve multi-character coherence while preserving narrative dynamism in sequential image generation.
A framework that combines MLLM-based image enhancement with a medium-aware 3D Gaussian Splatting model to reconstruct and render smoke scenes.
ID-Sim is a new similarity metric that aims to capture human selective sensitivity to identities by training on curated real and generative synthetic data and validating against human annotations on recognition, retrieval, and generative tasks.
citing papers explorer
-
When LoRA Betrays: Backdooring Text-to-Image Models by Masquerading as Benign Adapters
MasqLoRA shows that an independent LoRA adapter can be trained on a few trigger-target pairs to backdoor diffusion models with 99.8% success rate while remaining stealthy when the trigger is absent.
-
AttriStory: Fine-grained Attribute Realization for Visual Storytelling with Diffusion Models
AttriStory adds a benchmark and AttriLoss-based latent optimization to improve faithful rendering of fine-grained attributes such as clothing color and texture in diffusion-model visual storytelling.
-
Fashion130K: An E-commerce Fashion Dataset for Outfit Generation with Unified Multi-modal Condition
Fashion130K dataset and UMC framework align text and visual prompts to generate more consistent fashion outfits than prior state-of-the-art methods.
-
Gate-and-Merge: Zero-shot Compositional Personalization of Vision Language Models
Gate-and-Merge enables zero-shot compositional personalization of VLMs by independently learning concept-specific LoRA adapters and merging them in weight space with cue-based gating to suppress interference.
-
RealDiffusion: Physics-informed Attention for Multi-character Storybook Generation
RealDiffusion uses heat diffusion as a dissipative prior and a region-aware stochastic process inside a training-free physics-informed attention mechanism to improve multi-character coherence while preserving narrative dynamism in sequential image generation.
-
3D Smoke Scene Reconstruction Guided by Vision Priors from Multimodal Large Language Models
A framework that combines MLLM-based image enhancement with a medium-aware 3D Gaussian Splatting model to reconstruct and render smoke scenes.
-
ID-Sim: An Identity-Focused Similarity Metric
ID-Sim is a new similarity metric that aims to capture human selective sensitivity to identities by training on curated real and generative synthetic data and validating against human annotations on recognition, retrieval, and generative tasks.