ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2503.23234
32
0

Z-SASLM: Zero-Shot Style-Aligned SLI Blending Latent Manipulation

29 March 2025
Alessio Borgi
Luca Maiano
Irene Amerini
ArXivPDFHTML
Abstract

We introduce Z-SASLM, a Zero-Shot Style-Aligned SLI (Spherical Linear Interpolation) Blending Latent Manipulation pipeline that overcomes the limitations of current multi-style blending methods. Conventional approaches rely on linear blending, assuming a flat latent space leading to suboptimal results when integrating multiple reference styles. In contrast, our framework leverages the non-linear geometry of the latent space by using SLI Blending to combine weighted style representations. By interpolating along the geodesic on the hypersphere, Z-SASLM preserves the intrinsic structure of the latent space, ensuring high-fidelity and coherent blending of diverse styles - all without the need for fine-tuning. We further propose a new metric, Weighted Multi-Style DINO ViT-B/8, designed to quantitatively evaluate the consistency of the blended styles. While our primary focus is on the theoretical and practical advantages of SLI Blending for style manipulation, we also demonstrate its effectiveness in a multi-modal content fusion setting through comprehensive experimental studies. Experimental results show that Z-SASLM achieves enhanced and robust style alignment. The implementation code can be found at:this https URL.

View on arXiv
@article{borgi2025_2503.23234,
  title={ Z-SASLM: Zero-Shot Style-Aligned SLI Blending Latent Manipulation },
  author={ Alessio Borgi and Luca Maiano and Irene Amerini },
  journal={arXiv preprint arXiv:2503.23234},
  year={ 2025 }
}
Comments on this paper