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October 10, 2025Open Access

ConceptSplit: Decoupled Multi-Concept Personalization of Diffusion Models via Token-wise Adaptation and Attention Disentanglement

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Authors

HLH. LimYWYoungdo WonJSJu-Won Seo

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Overview

The framework ConceptSplit improves multi-concept personalization in diffusion models, suggesting that token-wise adaptation alleviates concept mixing.

Key Points

  • ConceptSplit effectively mitigates concept mixing in multi-concept personalizations, resulting in clearer image outputs.
  • The framework includes unique methods like Token-wise Value Adaptation and Latent Optimization to enhance attention mechanisms.
  • Empirical results indicate that existing methods disrupt attention, while ConceptSplit ensures coherent representation of multiple concepts.
  • This research represents a significant advancement in text-to-image synthesis, offering a solution to long-standing challenges in the field.

Cite This Study

Lim et al. (2025) studied this question.

synapsesocial.com/papers/68e997abe14057276da7f1d0https://doi.org/10.48550/arxiv.2510.04668
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