{"total":33,"rows":[{"id":"2209.04747","title":"Diffusion Models in Vision: A Survey","created":"2022-09-10","cited_by_count":1015,"area":"diffusion"},{"id":"2303.17591","title":"Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models","created":"2023-03-30","cited_by_count":301,"area":"diffusion"},{"id":"2209.02646","title":"A Survey on Generative Diffusion Model","created":"2022-09-06","cited_by_count":240,"area":"diffusion"},{"id":"2305.10657","title":"PTQD: Accurate Post-Training Quantization for Diffusion Models","created":"2023-05-18","cited_by_count":170,"area":"diffusion"},{"id":"2306.04542","title":"On the Design Fundamentals of Diffusion Models: A Survey","created":"2023-06-07","cited_by_count":60,"area":"diffusion"},{"id":"2305.18470","title":"Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation","created":"2023-05-29","cited_by_count":52,"area":"diffusion"},{"id":"2210.09292","title":"Efficient Diffusion Models for Vision: A Survey","created":"2022-10-07","cited_by_count":51,"area":"diffusion"},{"id":"2305.00562","title":"Class-Balancing Diffusion Models","created":"2023-04-30","cited_by_count":48,"area":"diffusion"},{"id":"2210.06462","title":"Self-Guided Diffusion Models","created":"2022-10-12","cited_by_count":37,"area":"diffusion"},{"id":"2410.15027","title":"Group Diffusion Transformers are Unsupervised Multitask Learners","created":"2024-10-19","cited_by_count":22,"area":"diffusion"},{"id":"2211.03264","title":"Few-shot Image Generation with Diffusion Models","created":"2022-11-07","cited_by_count":21,"area":"diffusion"},{"id":"2305.19094","title":"Diffusion Model for Dense Matching","created":"2023-05-30","cited_by_count":21,"area":"diffusion"},{"id":"2212.03221","title":"ADIR: Adaptive Diffusion for Image Reconstruction","created":"2022-12-06","cited_by_count":20,"area":"diffusion"},{"id":"2409.06065","title":"DiffusionPen: Towards Controlling the Style of Handwritten Text Generation","created":"2024-09-09","cited_by_count":16,"area":"diffusion"},{"id":"2302.10907","title":"Diffusion Models in Bioinformatics: A New Wave of Deep Learning Revolution in Action","created":"2023-02-13","cited_by_count":15,"area":"diffusion"},{"id":"2306.14153","title":"DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data","created":"2023-06-25","cited_by_count":15,"area":"diffusion"},{"id":"2306.08256","title":"Data Augmentation for Seizure Prediction with Generative Diffusion Model","created":"2023-06-14","cited_by_count":14,"area":"diffusion"},{"id":"2301.11722","title":"Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?","created":"2023-01-27","cited_by_count":10,"area":"diffusion"},{"id":"2303.06068","title":"EEG Synthetic Data Generation Using Probabilistic Diffusion Models","created":"2023-03-06","cited_by_count":8,"area":"diffusion"},{"id":"2506.07280","title":"From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models","created":"2025-06-08","cited_by_count":8,"area":"diffusion"},{"id":"2305.16269","title":"UDPM: Upsampling Diffusion Probabilistic Models","created":"2023-05-25","cited_by_count":5,"area":"diffusion"},{"id":"2502.04491","title":"Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning","created":"2025-02-06","cited_by_count":5,"area":"diffusion"},{"id":"2311.03959","title":"Improving the Effectiveness of Deep Generative Data","created":"2023-11-07","cited_by_count":4,"area":"diffusion"},{"id":"2311.10162","title":"Learning to Reconstruct Accelerated MRI Through K-space Cold Diffusion without Noise","created":"2023-11-16","cited_by_count":4,"area":"diffusion"},{"id":"2309.14756","title":"On quantifying and improving realism of images generated with diffusion","created":"2023-09-26","cited_by_count":3,"area":"diffusion"},{"id":"2403.05170","title":"DiffuLT: How to Make Diffusion Model Useful for Long-tail Recognition","created":"2024-03-08","cited_by_count":3,"area":"diffusion"},{"id":"2403.14429","title":"Style-Extracting Diffusion Models for Semi-Supervised Histopathology Segmentation","created":"2024-03-21","cited_by_count":3,"area":"diffusion"},{"id":"2406.06079","title":"Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks","created":"2024-06-10","cited_by_count":3,"area":"diffusion"},{"id":"2311.16353","title":"Improving Denoising Diffusion Probabilistic Models via Exploiting Shared Representations","created":"2023-11-27","cited_by_count":2,"area":"diffusion"},{"id":"2405.14857","title":"Conditional Diffusion on Web-Scale Image Pairs leads to Diverse Image Variations","created":"2024-05-23","cited_by_count":0,"area":"diffusion"},{"id":"2605.13386","title":"Support-Conditioned Flow Matching Is Kernel Smoothing","created":"2026-05-13","cited_by_count":0,"area":"diffusion"},{"id":"2607.16685","title":"Semi-Supervised Conditional Diffusion via Label Augmentation","created":"2026-07-18","cited_by_count":0,"area":"diffusion"},{"id":"2610.13690","title":"Transformer-based In-Context Score Operator Learning for Diffusion Models","created":"2026-10-09","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}