Prompt-aware weighting strategies W-Switch and W-Composite improve multi-concept LoRA composition in diffusion models without training.
Multlfg: Training-free multi-lora composi- tion using frequency-domain guidance
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
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.
citing papers explorer
-
Training-Free Multi-Concept LoRA Composition with Prompt-Aware Weighting
Prompt-aware weighting strategies W-Switch and W-Composite improve multi-concept LoRA composition in diffusion models without training.
-
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.