Licon MSR V1 is a multi-reference LoRA trained for LTX-2.5.
It uses the Multiple Subject Reference (MSR) approach to encode multiple reference images as visual tokens in the same latent space as the target video. Each reference is assigned a learned slot embedding and a distinct negative temporal position, allowing target video tokens to retrieve character, clothing, object, and scene information through the model's native self-attention layers.
Key Features
Supports up to five reference images
Preserves multiple characters, clothing, objects, and backgrounds
Learned slot embeddings distinguish different references
Native self-attention retrieval of reference details
Supports multi-subject and subject-object composition
Designed specifically for the LTX-2.5 architecture
Usage
ComfyUI inference requires ComfyUI-LTX2.5-MSR. A sample workflow is included in the plugin repository.
Usage Tips
Describe each reference image clearly in the prompt.
Use consistent labels such as Image 1, Image 2, and Image 3.
Clearly specify subject actions and spatial relationships.
Specify which reference provides the character, object, clothing, or background.
