Classifier-Free Guidance

Also known as CFG

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Latest papers 62

19 papers in the last four weeks, up 171% on the four weeks before. 0.1% of all new papers.

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Improving scDiffusion with Sparsity-Biased Classifier-Free Guidance
Jul 31, 2026Yu Song, Hao Sun, Ikuko Nishikawa +1Classifier-Free Guidance Diffusion Sampling
College of Information Science and Engineering, Ritsumeikan University, Osaka, Japan
Rethinking Classifier-Free Guidance in On-Policy Diffusion Distillation
Jul 27, 2026Bingnan Li, Haozhe Wang, Haozhong Xiong +5Diffusion Model Guidance Classifier-Free Guidance
Qwen Business Unit of Alibaba
Analytic Distribution of Classifier-Free Guidance for Schedule Design
Jul 22, 2026Enze Jiang, Zheng MaClassifier-Free Guidance Diffusion Sampling
School of Mathematical Sciences Shanghai Jiao Tong University Shanghai, China
Closing the Null Space: Guidance-Aware Quantization for Classifier-Free Diffusion
Jul 9, 2026Abdullah Al Shafi, Sumaiya Rahim SumaMixed-Precision Quantization Classifier-Free Guidance
Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna-9203, Bangladesh
Guidance Breaks the Fitted Operator: A Terminal-Fitted Repair for Classifier-Free Guidance
Jul 8, 2026Shiheng ZhangClassifier-Free Guidance Diffusion Sampling
University of Washington
When Does High-CFG Diffusion Inversion Fail? A Controlled Study of Prompt--Latent Interactions
Jul 6, 2026Yan Zeng, Yusuke Hosoya, Huyen T. T. Tran +1Diffusion Model Inversion Classifier-Free Guidance
GSIS Tohoku University Sendai, Japan · RIKEN AIP JAPAN
Joint Residual Reweighting for Classifier Free Guidance in Flow-Matching Zero-Shot TTS
Jun 24, 2026Runwu Shi, Yujin Wang, Hongjin Song +8Flow Matching Classifier-Free Guidance
Institute of Science Tokyo · Wuhan University · Beijing Institute of Technology +1
Information-Theoretic Classifier-Free Guidance with Adaptive Schedule Optimization
Jun 23, 2026Haobo Chen, Xiangxiang Xu, Yuheng BuDiffusion Model Guidance Classifier-Free Guidance
Department of Computer Science University of California, Santa Barbara · Department of Computer Science University of Rochester
DASH: Dual-Branch Score Distillation for Guidance-Calibrated Compact Diffusion Models
May 30, 2026Abdullah Al Shafi, Kazi Saeed Alam, Sk Imran Hossain +1Model Compression Classifier-Free Guidance
Khulna University of Engineering & Technology, Bangladesh · University Clermont Auvergne, France
PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion
May 27, 2026Łukasz Janisiów, Sebastian Musiał, Bartosz Zieliński +2Molecular Optimization Classifier-Free Guidance
Faculty of Mathematics and Computer Science, Jagiellonian University · Doctoral School of Exact and Natural Sciences, Jagiellonian University · Jagiellonian Center for Artificial Intelligence, Jagiellonian University +2
Stay Fair! Ensuring Group Fairness in Diffusion Models Across Guidance Scales
May 27, 2026Myeongsoo Kim, Eunji Kim, Minwoo Chae +1Diffusion Model Guidance Classifier-Free Guidance
1POSTECH · 2Amazon
Probability-Conserving Flow Guidance
May 19, 2026Parsa Esmati, Junha Hyung, Amirhossein Dadashzadeh +2Diffusion Model Guidance Classifier-Free Guidance
University of Bristol · KAIST
VAGS: Velocity Adaptive Guidance Scale for Image Editing and Generation
May 15, 2026Yan Luo, Ahmadou Aidara, Jingyi Lu +3Classifier-Free Guidance Diffusion-Based Image Generation
Harvard AI and Robotics Lab, Harvard University · School of Computing and Data Science, The University of Hong Kong · Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University
Guidance Is Not a Hyperparameter: Learning Dynamic Control in Diffusion Language Models
May 8, 2026Fan Zhou, Tim Van de CruysClassifier-Free Guidance Controllable Text Generation
KU Leuven
P-Guide: Parameter-Efficient Prior Steering for Single-Pass CFG Inference
May 7, 2026Xin Peng, Ang GaoFlow Matching Classifier-Free Guidance
School of Physical Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China
Delta Score Matters! Spatial Adaptive Multi Guidance in Diffusion Models
Apr 29, 2026Haosen Li, Wenshuo Chen, Lei Wang +4Diffusion Model Guidance Classifier-Free Guidance
1The Hong Kong University of Science and Technology (Guangzhou) · 2Griffith University & Data61/CSIRO
SPREG: Structured Plan Repair with Entropy-Guided Test-Time Intervention for Large Language Model Reasoning
Apr 20, 2026Xuan Wang, Yu Ming, Xinhao Zhong +4LLM Self-Correction Classifier-Free Guidance
1Meituan
Reward Weighted Classifier-Free Guidance as Policy Improvement in Autoregressive Models
Apr 16, 2026Alexander Peysakhovich, William BermanClassifier-Free Guidance Autoregressive Generation
∗Sutter Hill Ventures · †Sutter Hill Ventures
Post-Hoc Guidance for Consistency Models by Joint Flow Distribution Learning
Apr 10, 2026Chia-Hong Hsu, Randall BalestrieroConsistency Models Diffusion Model Guidance
Brown University
Not all tokens contribute equally to diffusion learning
Apr 8, 2026Guoqing Zhang, Lu Shi, Wanru Xu +4Diffusion Model Guidance Attention Control in Diffusion Models
State Key Laboratory of Advanced Rail Autonomous Operation, Bejing Jiaotong University, Beijing, China · School of Computer Science and Technology, Bejing Jiaotong University, Beijing, China · Visual Intellgence +X International Cooperation Joint Laboratory of MOE, Bejing Jiaotong University, Beijing, China +3
MCLR: Improving Conditional Modeling via Inter-Class Likelihood-Ratio Maximization and Unifying Classifier-Free Guidance with Alignment Objectives
Mar 23, 2026Xiang Li, Yixuan Jia, Xiao Li +3Conditional Diffusion Models Diffusion Model Alignment
University of Michigan · Michigan State University
Improving Diffusion Generalization with Weak-to-Strong Segmented Guidance
Mar 21, 2026Liangyu Yuan, Yufei Huang, Mingkun Lei +5Diffusion Model Guidance Diffusion Models
Westlake University · Tongji University · Zhejiang University +1
Setting-Matched and Semantics-Scaled Benchmarking of One-Step Generative Models Against Multistep Diffusion and Flow Models
Mar 15, 2026Advaith Ravishankar, Serena Liu, Mingyang Wang +11One-Step Generative Modeling Image Generation Evaluation
Harvard AI and Robotics Lab, Harvard University
Manifold-Optimal Guidance: A Unified Riemannian Control View of Diffusion Guidance
Mar 12, 2026Zexi Jia, Pengcheng Luo, Zhengyao Fang +2Diffusion Guidance Diffusion Models
WeChat AI, Tencent Inc., China.
Guiding Diffusion Models with Semantically Degraded Conditions
Mar 11, 2026Shilong Han, Yuming Zhang, Hongxia WangDiffusion Model Guidance T2I Diffusion Models
College of Science, National University of Defense Technology
C $^2$ FG: Control Classifier-Free Guidance via Score Discrepancy Analysis
Mar 9, 2026Jiayang Gao, Tianyi Zheng, Jiayang Zou +9Classifier-Free Guidance Inference-Time Guidance
Shanghai Jiao Tong University, Shanghai, China · vivo BlueImage Lab, vivo Mobile Communication Co., Ltd., China
CFG-Ctrl: Control-Based Classifier-Free Diffusion Guidance
Mar 3, 2026Hanyang Wang, Yiyang Liu, Jiawei Chi +3Diffusion Model Guidance Classifier-Free Guidance
Tsinghua University
Guidance Matters: Rethinking the Evaluation Pitfall for Text-to-Image Generation
Feb 26, 2026Dian Xie, Shitong Shao, Lichen Bai +5Diffusion Model Guidance T2I Generation Evaluation
The Hong Kong University of Science and Technology (Guangzhou) · Harbin Institute of Technology (Shenzhen) · Cogniser Information Technology
Rethinking Preference Alignment for Diffusion Models with Classifier-Free Guidance
Feb 21, 2026Zhou Jiang, Yandong Wen, Zhen LiuDiffusion Model Alignment Preference Alignment
Westlake University · The Chinese University of Hong Kong, Shenzhen
Flow Matching with Uncertainty Quantification and Guidance
Feb 10, 2026Juyeop Han, Lukas Lao Beyer, Sertac KaramanFlow Matching Image Generation
MIT

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Improving scDiffusion with Sparsity-Biased Classifier-Free Guidance

Yu Song, Hao Sun, Ikuko Nishikawa, Yen-Wei Chen

College of Information Science and Engineering, Ritsumeikan University, Osaka, Japan

Classifier-Free Guidance Diffusion Sampling Single-Cell RNA Sequencing

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Single-cell RNA sequencing (scRNA-seq) has become an essential tool in modern cellular biology, and generating accurate synthetic scRNA-seq data is becoming increasingly important. Although diffusion models have achieved promising results in conditional scRNA-seq generation, existing guidance strategies, including classifier guidance and classifier-free guidance (CFG), rely on an unconditional branch trained to approximate the true marginal distribution, which may retain substantial gene-specific structure and limit guidance effectiveness. Inspired by recent work showing that diffusion models can be effectively guided using intentionally degraded references, we propose a sparsity-biased classifier-free guidance (SB-CFG) strategy for scRNA-seq generation. Rather than approximating the assumed "neutral" marginal distribution, SB-CFG introduces a deliberately under-informative sparse reference for the unconditional branch, removing gene identity while preserving only coarse sparsity statistics. This "bad" reference amplifies the contrast between conditional and unconditional predictions, leading to stronger and more effective guidance during sampling. We evaluated SB-CFG as a training-free sampling modification on five publicly available scRNA-seq datasets. Experimental results demonstrate consistent improvements over standard CFG-based sampling in terms of marker gene expression fidelity, cell-type consistency, and sparsity preservation, indicating that SB-CFG better captures biologically meaningful gene expression patterns.