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

Example 03

Example 06

Example 07

Reference Images

MiniMax H3

Licon MSR V1

Reference Images

MiniMax H3

Licon MSR V1

Reference Images

MiniMax H3

Licon MSR V1