{"total":45,"rows":[{"id":"2505.13447","title":"Mean Flows for One-step Generative Modeling","created":"2025-05-19","cited_by_count":561,"area":null},{"id":"2602.04770","title":"Generative Modeling via Drifting","created":"2026-02-04","cited_by_count":116,"area":null},{"id":"2512.02012","title":"Improved Mean Flows: On the Challenges of Fastforward Generative Models","created":"2025-12-01","cited_by_count":110,"area":null},{"id":"2601.22158","title":"One-step Latent-free Image Generation with Pixel Mean Flows","created":"2026-01-29","cited_by_count":53,"area":null},{"id":"2604.28190","title":"Representation Fr\\'echet Loss for Visual Generation","created":"2026-04-30","cited_by_count":37,"area":null},{"id":"2510.14974","title":"pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation","created":"2025-10-16","cited_by_count":29,"area":null},{"id":"2510.24474","title":"Decoupled MeanFlow: Turning Flow Models into Flow Maps for Accelerated Sampling","created":"2025-10-28","cited_by_count":20,"area":null},{"id":"2512.02636","title":"Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models","created":"2025-12-02","cited_by_count":18,"area":null},{"id":"2603.10592","title":"Gradient Flow Drifting: Generative Modeling via Wasserstein Gradient Flows of KDE-Approximated Divergences","created":"2026-03-11","cited_by_count":17,"area":null},{"id":"2511.19428","title":"Flow Map Distillation Without Data","created":"2025-11-24","cited_by_count":14,"area":null},{"id":"2511.22475","title":"Adversarial Flow Models","created":"2025-11-27","cited_by_count":12,"area":null},{"id":"2605.05118","title":"On the Wasserstein Gradient Flow Interpretation of Drifting Models","created":"2026-05-06","cited_by_count":11,"area":null},{"id":"2607.02375","title":"Representation Distribution Matching for One-Step Visual Generation","created":"2026-07-02","cited_by_count":11,"area":null},{"id":"2512.10953","title":"Bidirectional Normalizing Flow: From Data to Noise and Back","created":"2025-12-11","cited_by_count":7,"area":null},{"id":"2512.13255","title":"B\\'ezierFlow: Learning B\\'ezier Stochastic Interpolant Schedulers for Few-Step Generation","created":"2025-12-15","cited_by_count":7,"area":null},{"id":"2510.21250","title":"Improved Training Technique for Shortcut Models","created":"2025-10-24","cited_by_count":6,"area":null},{"id":"2509.24935","title":"Scalable GANs with Transformers","created":"2025-09-29","cited_by_count":5,"area":null},{"id":"2510.02110","title":"SoundReactor: Frame-level Online Video-to-Audio Generation","created":"2025-10-02","cited_by_count":5,"area":null},{"id":"2510.03597","title":"Neon: Negative Extrapolation From Self-Training Improves Image Generation","created":"2025-10-04","cited_by_count":5,"area":null},{"id":"2603.07276","title":"Variational Flow Maps: Make Some Noise for One-Step Conditional Generation","created":"2026-03-07","cited_by_count":5,"area":null},{"id":"2511.19065","title":"Understanding, Accelerating, and Improving MeanFlow Training","created":"2025-11-24","cited_by_count":4,"area":null},{"id":"2602.17682","title":"Duality Models: An Embarrassingly Simple One-step Generation Paradigm","created":"2026-02-04","cited_by_count":3,"area":null},{"id":"2605.12183","title":"DriftXpress: Faster Drifting Models via Projected RKHS Fields","created":"2026-05-12","cited_by_count":3,"area":null},{"id":"2605.26552","title":"Aligning Few-Step Generative Models by Amortizing Sample-based Variational Inference","created":"2026-05-26","cited_by_count":3,"area":null},{"id":"2606.15553","title":"Distilling Drifting Transformers with Representation Autoencoders","created":"2026-06-14","cited_by_count":3,"area":null},{"id":"2510.14666","title":"Geometric Moment Alignment for Domain Adaptation via Siegel Embeddings","created":"2025-10-16","cited_by_count":2,"area":null},{"id":"2602.02571","title":"Trajectory Consistency for One-Step Generation on Euler Mean Flows","created":"2026-01-31","cited_by_count":2,"area":null},{"id":"2602.08859","title":"Magnitude Distance: A Geometric Measure of Dataset Similarity","created":"2026-02-09","cited_by_count":2,"area":null},{"id":"2606.22527","title":"Trajectory Forcing: Structure-First Generation with Controllable Semantic Trajectories","created":"2026-06-21","cited_by_count":2,"area":null},{"id":"2607.24235","title":"Minimax Lower Bounds of Kernel Discrepancy Estimation: MMD, HSIC, KSD","created":"2026-07-27","cited_by_count":2,"area":null},{"id":"2607.26860","title":"Amortized Moment Matching for Visual Generation","created":"2026-07-29","cited_by_count":2,"area":null},{"id":"2605.25107","title":"Leveraging Gauge Freedom for Learning Non-Gradient Population Dynamics of Stochastic Systems","created":"2026-05-24","cited_by_count":1,"area":null},{"id":"2605.29194","title":"Stochastic Lifting for Generating Trajectories of Stochastic Physical Systems","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2510.12636","title":"Adapting Noise to Data: Generative Flows from 1D Processes","created":"2025-10-14","cited_by_count":0,"area":null},{"id":"2511.23342","title":"Overcoming the Curvature Bottleneck in MeanFlow","created":"2025-11-28","cited_by_count":0,"area":null},{"id":"2602.06346","title":"FlowConsist: Make Your Flow Consistent with Real Trajectory","created":"2026-02-06","cited_by_count":0,"area":null},{"id":"2604.24586","title":"Point-MF: Stabilizing One-Step Mean Flows for Single-Image Point Cloud Reconstruction","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2605.05540","title":"Autoregressive One-Step Generative Modeling for Dynamical System Forecasting","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.15309","title":"One Pass Is Not Enough: Recursive Latent Refinement for Generative Models","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2609.26435","title":"One-Step Generative Surrogate Models via Block-Triangular Joint Drifting","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2609.35512","title":"Improving Generative Model Self-Training with Geometrically Modified Outputs","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2610.02208","title":"Sphere Encoder 2","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.03626","title":"Depth as Time in One-Step Generative Models","created":"2026-10-02","cited_by_count":0,"area":null},{"id":"2610.13625","title":"Kernel-based External Validity of Experimental Studies","created":"2026-10-09","cited_by_count":0,"area":null},{"id":"2610.18552","title":"Unbalanced W-Flow: Unbalanced Wasserstein Drifting under Finite-Batch Marginal Fluctuations","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}