mlsanityData to 14 Oct 2026

LAMS-Edit: Latent and Attention Mixing with Schedulers for Improved Content Preservation in Diffusion-Based Image and Style Editing

arXiv 2601.02987 ↗First posted 6 Jan 2026cs.CV cs.AIcited by 0

On the map: Diffusion models → Image generation, text-to-image and editing

Abstract (arXiv)

Text-to-Image editing using diffusion models faces challenges in balancing content preservation with edit application and handling real-image editing. To address these, we propose LAMS-Edit, leveraging intermediate states from the inversion process--an essential step in real-image editing--during edited image generation. Specifically, latent representations and attention maps from both processes are combined at each step using weighted interpolation, controlled by a scheduler. This technique, Latent and Attention Mixing with Schedulers (LAMS), integrates with Prompt-to-Prompt (P2P) to form LAMS-Edit--an extensible framework that supports precise editing with region masks and enables style transfer via LoRA. Extensive experiments demonstrate that LAMS-Edit effectively balances content preservation and edit application.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 46 of its 49 references that are in the map. First posted on arXiv 6 Jan 2026.

Builds on

46 of 49 references.

Closest ancestors · 25

Same direction, newest first

  1. 2024Dual-Schedule Inversion: Training- and Tuning-Free Inversion for Real Image Editing15 Dec
  2. 2024TiNO-Edit: Timestep and Noise Optimization for Robust Diffusion-Based Image Editing17 Apr
  3. 2024Towards Understanding Cross and Self-Attention in Stable Diffusion for Text-Guided Image Editing6 Mar
  4. 2024Towards Efficient Diffusion-Based Image Editing with Instant Attention Masks15 Jan
  5. 2023Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models19 Dec
  6. 2023LIME: Localized Image Editing via Attention Regularization in Diffusion Models14 Dec
  7. 2023LEDITS++: Limitless Image Editing using Text-to-Image Models28 Nov
  8. 2023InstructEdit: Improving Automatic Masks for Diffusion-based Image Editing With User Instructions29 May
  9. 2023Prompt Tuning Inversion for Text-Driven Image Editing Using Diffusion Models8 May
  10. 2023Guided Image Synthesis via Initial Image Editing in Diffusion Model5 May
  11. 2023Adding Conditional Control to Text-to-Image Diffusion Models10 Feb
  12. 2023GLIGEN: Open-Set Grounded Text-to-Image Generation17 Jan
13 more
  1. 2022Uncovering the Disentanglement Capability in Text-to-Image Diffusion Models16 Dec
  2. 2022Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis9 Dec
  3. 2022SINE: SINgle Image Editing with Text-to-Image Diffusion Models8 Dec
  4. 2022Shape-Guided Diffusion with Inside-Outside Attention1 Dec
  5. 2022Paint by Example: Exemplar-based Image Editing with Diffusion Models23 Nov
  6. 2022Inversion-Based Style Transfer with Diffusion Models23 Nov
  7. 2022InstructPix2Pix: Learning to Follow Image Editing Instructions17 Nov
  8. 2022Null-text Inversion for Editing Real Images using Guided Diffusion Models17 Nov
  9. 2022DiffEdit: Diffusion-based semantic image editing with mask guidance20 Oct
  10. 2022Imagic: Text-Based Real Image Editing with Diffusion Models17 Oct
  11. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation25 Aug
  12. 2022Blended Latent Diffusion6 Jun
  13. 2021Blended Diffusion for Text-driven Editing of Natural Images29 Nov

Other references · 21

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  4. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  5. 2020Denoising Diffusion Implicit Modelscited by 9,781
  6. 2023Segment Anythingcited by 8,234
  7. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,431
  8. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,245
  9. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,937
  10. 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translationcited by 906
  11. 2023MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editingcited by 727
  12. 2023Zero-shot Image-to-Image Translationcited by 505
9 more
  1. 2022Text2LIVE: Text-Driven Layered Image and Video Editingcited by 312
  2. 2023Diffusion Self-Guidance for Controllable Image Generationcited by 305
  3. 2022EDICT: Exact Diffusion Inversion via Coupled Transformationscited by 258
  4. 2023Diffusion Models Generate Images Like Painters: an Analytical Theory of Outline First, Details Latercited by 55
  5. 2024Boosting Diffusion Models with Moving Average Sampling in Frequency Domaincited by 55
  6. 2022DiffStyler: Controllable Dual Diffusion for Text-Driven Image Stylizationcited by 45
  7. 2023General Image-to-Image Translation with One-Shot Image Guidancecited by 31
  8. 2023Adaptive Guidance: Training-free Acceleration of Conditional Diffusion Modelscited by 31
  9. 2024Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysiscited by 19

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  2. 2025Tuning-Free Image Editing with Fidelity and Editability via Unified Latent Diffusion Model
  3. 2025Structure-Preserving Zero-Shot Image Editing via Stage-Wise Latent Injection in Diffusion Models
  4. 2026Editing on the Generative Manifold: A Theoretical and Empirical Study of General Diffusion-Based Image Editing Trade-offs
  5. 2024Task-Oriented Diffusion Inversion for High-Fidelity Text-based Editing
  6. 2025Self-Attention Decomposition For Training Free Diffusion Editing
  7. 2023Textual and Visual Prompt Fusion for Image Editing via Step-Wise Alignment
  8. 2025Training-Free Style and Content Transfer by Leveraging U-Net Skip Connections in Stable Diffusion