T2I Diffusion Models

T2I: Text-to-Image

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AI-T2I: Aggregating-and-Isolating Cross-Attention to Diffusion Models for Text-to-Image Synthesis
May 25, 2026Shipeng Cao, Biao Qian, Haipeng Liu +2Diffusion Model Alignment Cross-Attention
Key Laboratory of Knowledge Engineering With Big Data, Ministry of Education, Hefei University of Technology, China · Department of Automation, Tsinghua University, China
Towards Anatomically Plausible Human Image Generation via Synthetic Localized Preferences
May 25, 2026Bao Li, Yuliang Xiu, Zhen LiuDiffusion Model Alignment Direct Preference Optimization
Westlake University · The Chinese University of Hong Kong, Shenzhen
DRM: Diffusion-based Reward Model With Step-wise Guidance
May 25, 2026Jaxon Zhang, Binxin Yang, Hubery Yin +2Diffusion Model Alignment Diffusion Model Guidance
Peking University · Work done during an internship at WeChat Vision, Tencent Inc. · WeChat Vision, Tencent Inc.
ERNIE-Image Technical Report
May 25, 2026Jiaxiang Liu, Zhida Feng, Pengyu Zou +46Personalized Image Aesthetics Assessment Diffusion Model Distillation
Injecting Image Guidance into Text-Conditioned Diffusion Models at Inference
May 24, 2026Agata Żywot, Iason Skylitsis, Thijmen Nijdam +4Diffusion Model Guidance Test-Time Optimization
University of Amsterdam, Netherlands
Composing People Together: Iterative Pose-Image Generation for Multi-Person Interaction Scenes
May 22, 2026Wenxuan Peng, Bharath Hariharan, Hadar Averbuch-ElorImage Generation Compositional Image Generation
Cornell University, Ithaca, USA · Cornell University, New York, New York, USA
SeqLoRA: Bilevel Orthogonal Adaptation for Continual Multi-Concept Generation
May 21, 2026Javad Parsa, Enis Simsar, Amir Joudaki +2Subject-Driven Image Generation Diffusion Model Fine-Tuning
ETH Zurich · Uppsala University, Sweden
SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers
May 21, 2026Javad Rajabi, Kimia Shaban, Koorosh Roohi +2Rotary Positional Embeddings Diffusion Model Guidance
University of Toronto · Vector Institute
Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models
May 20, 2026Dong Chen, Fangyun Wei, Ziyu Wan +18Multimodal Foundation Models T2I Diffusion Models
Microsoft Lens Team
MONET: A Massive, Open, Non-redundant and Enriched Text-to-image dataset
May 20, 2026Benjamin Aubin, Gonzalo Iñaki Quintana, Onur Tasar +4Training Data Curation T2I Generation
Jasper Research
Spatial Gram Alignment for Ultra-High-Resolution Image Synthesis
May 20, 2026Jinjin Zhang, Xiefan Guo, Di HuangDiffusion Model Alignment Latent Diffusion Models
Beihang University
Pareto-Enhanced Portrait Generation: Vision-Aligned Text Supervision for Alignment, Realism, and Aesthetics
May 20, 2026Yunlong Wang, Jinjin Shi, Wenbin Gao +3Diffusion Model Alignment Diffusion Transformer
Xiaomi Corporation Nanjing, China · Xiaomi Corporation Beijing, China
FullFlow: Upgrading Text-to-Image Flow Matching Models for Bidirectional Vision--Language Generation
May 19, 2026Eric Tillmann Bill, Enis Simsar, Alessio Tonioni +1Flow Matching Image Captioning
ETH Zurich · Google
Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-to-Image Diffusion Models
May 19, 2026Kai Wang, Jiale Zhang, Chengcheng Zhu +2Backdoor Attacks Diffusion Model Fine-Tuning
Yangzhou University · Nanjing University · Chongqing University +1
Self-Creative Text-to-Object Generation using Semantic-Aware Spatial Weighting
May 19, 2026Yue Yu, Haibo Chen, Shuo Chen +2T2I Generation Computational Creativity
Nanjing University of Science and Technology · Nanjing University
Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection
May 19, 2026Yunzhe Zhang, Hongfu Liu, Pengyu HongDiffusion Model Alignment T2I Generation
Brandeis University
Diff-Instruct with Diffused Reward: Towards Principled One-step Generator RL
May 18, 2026Junyi Wu, Weijian Luo, Haoyang Zheng +2Diffusion Model Alignment One-Step Generative Modeling
Purdue University · hi-lab, Xiaohongshu Inc.
SafeDiffusion-R1: Online Reward Steering for Safe Diffusion Post-Training
May 18, 2026Komal Kumar, Ankan Deria, Abhishek Basu +3Diffusion Model Alignment Diffusion Model Fine-Tuning
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), UAE · Michigan State University (MSU), USA
Stabilizing, Scaling & Enhancing MeanFlow for Large-scale Diffusion Distillation
May 18, 2026Xiao He, Yang Li, Peizhen Zhang +3Flow Matching Diffusion Model Distillation
1State Key Laboratory of Integrated Services Networks, Xidian University · 2Tencent Hunyuan
The Silent Brush: Evaluating Artistic Style Leakage in AI Art Generation
May 17, 2026Ninad Joshi, Ashutosh Ranjan, Vivek Srivastava +1T2I Generation T2I Generation Evaluation
TCS Research, India
Training-Free Occluded Text Rendering via Glyph Priors and Attention-Guided Semantic Blending
May 16, 2026Jingqi Hou, Hongtian WangCompositional T2I Generation Diffusion-Based Image Editing
1,2College of Computer Science, Beijing University of Technology, Beijing, China
Accelerating Rectified Flow Models via Trajectory-Aware Caching
May 16, 2026Xiao Liu, Kai Liu, Naiyang Guan +5Video Diffusion Models Rectified Flow
Shanghai Jiao Tong University, Shanghai, China · Academy of Military Science, Beijing, China · Huawei Technologies Ltd, Shenzhen, China
DiRotQ: Rotation-Aware Quantization for 4-bit Diffusion Transformers
May 16, 2026Sayeh Sharify, Mahsa Salmani, Hesham MostafaDiffusion Transformer Diffusion Model Quantization
d-Matrix Santa Clara, CA 95054
Unlocking Complex Visual Generation via Closed-Loop Verified Reasoning
May 14, 2026Hanbo Cheng, Limin Lin, Ruo Zhang +2Image Generation Compositional T2I Generation
University of Science and Technology of China (USTC) · 2Independent Researcher
Diagnosing and Correcting Concept Omission in Multimodal Diffusion Transformers
May 14, 2026Kanghyun Baek, Jaihyun Lew, Chaehun Shin +2Diffusion Transformer T2I Generation
Interdisciplinary Program in Artificial Intelligence, Seoul National University, Seoul, South Korea · Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea · Department of Computer Science & Engineering, Korea University, Seoul, South Korea +1
Pareto-Guided Optimal Transport for Multi-Reward Alignment
May 13, 2026Ying Ba, Tianyu Zhang, Mohan Zhou +5Diffusion Model Alignment Reward Hacking
Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China · Beijing Key Laboratory of Research on Large Models and Intelligent Governance · Engineering Research Center of Next-Generation Intelligent Search and Recommendation, MOE 4Tomorrow Advancing Life +2
Disentangled Sparse Representations for Concept-Separated Diffusion Unlearning
May 12, 2026Hyeonjin Kim, Hangyeol Jung, Heechan Yun +2Disentangled Representation Learning Sparse Autoencoders
Yonsei University · Kookmin University
STRIDE: Training-Free Diversity Guidance via PCA-Directed Feature Perturbation in Single-Step Diffusion Models
May 12, 2026Ankit Yadav, Arpit Garg, Ta Duc Huy +1Diffusion Model Guidance One-Step Generative Modeling
Australian Institute for Machine Learning, Adelaide University, Australia
Efficient Adjoint Matching for Fine-tuning Diffusion Models
May 12, 2026Jeongwoo Shin, Dongsoo Shin, Yuchen Zhu +5Diffusion Model Alignment Stochastic Optimal Control
Seoul National University · Georgia Institute of Technology · Sungkyunkwan University
HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer
May 11, 2026Qi Cai, Jingwen Chen, Chengmin Gao +22Diffusion Transformer Text-Guided Image Editing

May 25, 2026, cs.CVJ/K move · Enter open · S save

AI-T2I: Aggregating-and-Isolating Cross-Attention to Diffusion Models for Text-to-Image Synthesis

Shipeng Cao, Biao Qian, Haipeng Liu, Yang Wang+1

Key Laboratory of Knowledge Engineering With Big Data, Ministry of Education, Hefei University of Technology, China · Department of Automation, Tsinghua University, China

Diffusion Model Alignment Cross-Attention Attention Control in Diffusion Models Compositional T2I Generation T2I Diffusion Models

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Text-to-image synthesis has made significant progress, benefiting from the strong generative capabilities of diffusion models. However, these models struggle to achieve precise text-to-image alignment within cross-attention maps during the denoising process. Existing works primarily focus on inter-subject-token activations (i.e., cross-attention scores) overlap for different subjects, overlooking the intra-subject-token activations scattering issue for identical subjects. In this paper, we propose an Aggregating-and-Isolating cross-attention approach to diffusion models for Text-to-Image synthesis, dubbed AI-T2I. Technically, to address the scattering issue, we devise an aggregation loss to identify and consolidate the scattered intra-token activations, which implicitly helps mitigate the potential overlap issue. Upon that, an isolation loss is further introduced to push the inter-token activations apart, thus fulfilling precise text-to-image alignment. Extensive experiments on various benchmarks demonstrate the superiority of AI-T2I over the state-of-the-art works for text-to-image synthesis. Furthermore, our AI-T2I exhibits excellent generalization across other tasks, e.g., controllable layout generation and personalized generation. Our code is available at https://github.com/Hatter77/AI-T2I.

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