Licon MSR V1 for LTX-2.5
Overview
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.
Examples