{"total":367,"rows":[{"id":"2303.08797","title":"Stochastic Interpolants: A Unifying Framework for Flows and Diffusions","created":"2023-03-15","cited_by_count":939,"area":null},{"id":"2412.01506","title":"Structured 3D Latents for Scalable and Versatile 3D Generation","created":"2024-12-02","cited_by_count":770,"area":null},{"id":"2505.13447","title":"Mean Flows for One-step Generative Modeling","created":"2025-05-19","cited_by_count":561,"area":null},{"id":"2506.18871","title":"OmniGen2: Towards Instruction-Aligned Multimodal Generation","created":"2025-06-23","cited_by_count":253,"area":null},{"id":"2412.08629","title":"FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models","created":"2024-12-11","cited_by_count":217,"area":null},{"id":"2406.01572","title":"Unlocking Guidance for Discrete State-Space Diffusion and Flow Models","created":"2024-06-03","cited_by_count":129,"area":null},{"id":"2503.19325","title":"Long-Context Autoregressive Video Modeling with Next-Frame Prediction","created":"2025-03-25","cited_by_count":123,"area":null},{"id":"2402.06121","title":"Iterated Denoising Energy Matching for Sampling from Boltzmann Densities","created":"2024-02-09","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":"2310.03725","title":"Stochastic interpolants with data-dependent couplings","created":"2023-10-05","cited_by_count":100,"area":null},{"id":"2210.06662","title":"Action Matching: Learning Stochastic Dynamics from Samples","created":"2022-10-13","cited_by_count":98,"area":null},{"id":"2504.07963","title":"PixelFlow: Pixel-Space Generative Models with Flow","created":"2025-04-10","cited_by_count":97,"area":null},{"id":"2410.02711","title":"NETS: A Non-Equilibrium Transport Sampler","created":"2024-10-03","cited_by_count":69,"area":null},{"id":"2403.13724","title":"Probabilistic Forecasting with Stochastic Interpolants and F\\\"ollmer Processes","created":"2024-03-20","cited_by_count":66,"area":null},{"id":"2503.00710","title":"Proteina: Scaling Flow-based Protein Structure Generative Models","created":"2025-03-02","cited_by_count":65,"area":null},{"id":"2309.09968","title":"Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees","created":"2023-09-18","cited_by_count":62,"area":null},{"id":"2504.07943","title":"HoloPart: Generative 3D Part Amodal Segmentation","created":"2025-04-10","cited_by_count":60,"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":"2409.17808","title":"Generative Modeling of Molecular Dynamics Trajectories","created":"2024-09-26","cited_by_count":51,"area":null},{"id":"2310.10649","title":"A Computational Framework for Solving Wasserstein Lagrangian Flows","created":"2023-10-16","cited_by_count":46,"area":null},{"id":"2406.14426","title":"Transferable Boltzmann Generators","created":"2024-06-20","cited_by_count":46,"area":null},{"id":"2301.07388","title":"Learning Interpolations between Boltzmann Densities","created":"2023-01-18","cited_by_count":43,"area":null},{"id":"2410.22388","title":"ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation","created":"2024-10-29","cited_by_count":43,"area":null},{"id":"2306.06626","title":"On Kinetic Optimal Probability Paths for Generative Models","created":"2023-06-11","cited_by_count":42,"area":null},{"id":"2406.07266","title":"SemlaFlow -- Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matching","created":"2024-06-11","cited_by_count":41,"area":null},{"id":"2305.10690","title":"Sampling, Diffusions, and Stochastic Localization","created":"2023-05-18","cited_by_count":40,"area":null},{"id":"2310.02233","title":"Generalized Schr\\\"odinger Bridge Matching","created":"2023-10-03","cited_by_count":40,"area":null},{"id":"2312.02027","title":"Stochastic Optimal Control Matching","created":"2023-12-04","cited_by_count":40,"area":null},{"id":"2212.14424","title":"Normalizing flow neural networks by JKO scheme","created":"2022-12-29","cited_by_count":39,"area":null},{"id":"2310.03575","title":"Analysis of learning a flow-based generative model from limited sample complexity","created":"2023-10-05","cited_by_count":38,"area":null},{"id":"2502.18462","title":"Scalable Equilibrium Sampling with Sequential Boltzmann Generators","created":"2025-02-25","cited_by_count":38,"area":null},{"id":"2601.14430","title":"Meta Flow Maps enable scalable reward alignment","created":"2026-01-20","cited_by_count":37,"area":null},{"id":"2308.16212","title":"RetroBridge: Modeling Retrosynthesis with Markov Bridges","created":"2023-08-30","cited_by_count":36,"area":null},{"id":"2503.07535","title":"LBM: Latent Bridge Matching for Fast Image-to-Image Translation","created":"2025-03-10","cited_by_count":36,"area":null},{"id":"2512.01809","title":"Much Ado About Noising: Dispelling the Myths of Generative Robotic Control","created":"2025-12-01","cited_by_count":36,"area":null},{"id":"2310.17582","title":"Convergence of flow-based generative models via proximal gradient descent in Wasserstein space","created":"2023-10-26","cited_by_count":34,"area":null},{"id":"2406.00735","title":"Full-Atom Peptide Design based on Multi-modal Flow Matching","created":"2024-06-02","cited_by_count":34,"area":null},{"id":"2411.15843","title":"Unveil Inversion and Invariance in Flow Transformer for Versatile Image Editing","created":"2024-11-24","cited_by_count":34,"area":null},{"id":"2311.15100","title":"Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation","created":"2023-11-25","cited_by_count":33,"area":null},{"id":"2410.00844","title":"Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport","created":"2024-10-01","cited_by_count":33,"area":null},{"id":"2503.10772","title":"FlowTok: Flowing Seamlessly Across Text and Image Tokens","created":"2025-03-13","cited_by_count":33,"area":null},{"id":"2409.15278","title":"PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions","created":"2024-09-23","cited_by_count":31,"area":null},{"id":"2502.10843","title":"LEAPS: A discrete neural sampler via locally equivariant networks","created":"2025-02-15","cited_by_count":31,"area":null},{"id":"2310.05764","title":"Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design","created":"2023-10-09","cited_by_count":30,"area":null},{"id":"2410.05431","title":"Continuous Ensemble Weather Forecasting with Diffusion models","created":"2024-10-07","cited_by_count":30,"area":null},{"id":"2507.09466","title":"La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching","created":"2025-07-13","cited_by_count":30,"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":"2604.09784","title":"Discrete Flow Maps","created":"2026-04-10","cited_by_count":29,"area":null},{"id":"2304.13534","title":"A mean-field games laboratory for generative modeling","created":"2023-04-26","cited_by_count":28,"area":null},{"id":"2504.01647","title":"FlowR: Flowing from Sparse to Dense 3D Reconstructions","created":"2025-04-02","cited_by_count":28,"area":null},{"id":"2308.14085","title":"Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective","created":"2023-08-27","cited_by_count":26,"area":null},{"id":"2310.16624","title":"Free-form Flows: Make Any Architecture a Normalizing Flow","created":"2023-10-25","cited_by_count":26,"area":null},{"id":"2601.02358","title":"VINO: A Unified Visual Generator with Interleaved OmniModal Context","created":"2026-01-05","cited_by_count":26,"area":null},{"id":"2404.04240","title":"Dynamic Conditional Optimal Transport through Simulation-Free Flows","created":"2024-04-05","cited_by_count":25,"area":null},{"id":"2503.22677","title":"DSO: Aligning 3D Generators with Simulation Feedback for Physical Soundness","created":"2025-03-28","cited_by_count":25,"area":null},{"id":"2503.09817","title":"Temporal Difference Flows","created":"2025-03-12","cited_by_count":24,"area":null},{"id":"2512.04562","title":"LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative Models","created":"2025-12-04","cited_by_count":23,"area":null},{"id":"2402.17888","title":"ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection","created":"2024-02-27","cited_by_count":22,"area":null},{"id":"2510.02300","title":"Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models","created":"2025-10-02","cited_by_count":21,"area":null},{"id":"2603.28088","title":"GEMS: Agent-Native Multimodal Generation with Memory and Skills","created":"2026-03-30","cited_by_count":21,"area":null},{"id":"2502.14844","title":"Dynamic Concepts Personalization from Single Videos","created":"2025-02-20","cited_by_count":20,"area":null},{"id":"2504.10564","title":"FLOWR: Flow Matching for Structure-Aware De Novo, Interaction- and Fragment-Based Ligand Generation","created":"2025-04-14","cited_by_count":18,"area":null},{"id":"2505.04320","title":"Multi-turn Consistent Image Editing","created":"2025-05-07","cited_by_count":18,"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":"2301.13737","title":"Self-Consistent Velocity Matching of Probability Flows","created":"2023-01-31","cited_by_count":17,"area":null},{"id":"2310.03695","title":"Multimarginal generative modeling with stochastic interpolants","created":"2023-10-05","cited_by_count":17,"area":null},{"id":"2311.11475","title":"Gaussian Interpolation Flows","created":"2023-11-20","cited_by_count":17,"area":null},{"id":"2410.17270","title":"MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks","created":"2024-10-07","cited_by_count":17,"area":null},{"id":"2410.04081","title":"Epsilon-VAE: Denoising as Visual Decoding","created":"2024-10-05","cited_by_count":16,"area":null},{"id":"2410.09667","title":"EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants","created":"2024-10-12","cited_by_count":16,"area":null},{"id":"2504.11516","title":"FEAT: Free energy Estimators with Adaptive Transport","created":"2025-04-15","cited_by_count":16,"area":null},{"id":"2506.03131","title":"Native-Resolution Image Synthesis","created":"2025-06-03","cited_by_count":15,"area":null},{"id":"2603.08703","title":"HiAR: Efficient Autoregressive Long Video Generation via Hierarchical Denoising","created":"2026-03-09","cited_by_count":15,"area":null},{"id":"2503.15855","title":"VideoRFSplat: Direct Scene-Level Text-to-3D Gaussian Splatting Generation with Flexible Pose and Multi-View Joint Modeling","created":"2025-03-20","cited_by_count":14,"area":null},{"id":"2511.19428","title":"Flow Map Distillation Without Data","created":"2025-11-24","cited_by_count":14,"area":null},{"id":"2502.02300","title":"Density Ratio Estimation with Conditional Probability Paths","created":"2025-02-04","cited_by_count":13,"area":null},{"id":"2512.09914","title":"FALCON: Few-step Accurate Likelihoods for Continuous Flows","created":"2025-12-10","cited_by_count":13,"area":null},{"id":"2407.11734","title":"Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen","created":"2024-07-16","cited_by_count":12,"area":null},{"id":"2506.01955","title":"Dual-Process Image Generation","created":"2025-06-02","cited_by_count":12,"area":null},{"id":"2507.00899","title":"TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Quality","created":"2025-07-01","cited_by_count":12,"area":null},{"id":"2604.08503","title":"Phantom: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics","created":"2026-04-09","cited_by_count":12,"area":null},{"id":"2504.11478","title":"Flux Already Knows -- Activating Subject-Driven Image Generation without Training","created":"2025-04-12","cited_by_count":11,"area":null},{"id":"2505.18190","title":"PhySense: Sensor Placement Optimization for Accurate Physics Sensing","created":"2025-05-19","cited_by_count":11,"area":null},{"id":"2506.05526","title":"On Fitting Flow Models with Large Sinkhorn Couplings","created":"2025-06-05","cited_by_count":11,"area":null},{"id":"2510.13454","title":"Text-to-3D by Stitching a Multi-view Reconstruction Network to a Video Generator","created":"2025-10-15","cited_by_count":11,"area":null},{"id":"2502.09611","title":"Designing a Conditional Prior Distribution for Flow-Based Generative Models","created":"2025-02-13","cited_by_count":10,"area":null},{"id":"2505.17914","title":"Flexible MOF Generation with Torsion-Aware Flow Matching","created":"2025-05-23","cited_by_count":10,"area":null},{"id":"2312.05579","title":"Conditional Stochastic Interpolation for Generative Learning","created":"2023-12-09","cited_by_count":9,"area":null},{"id":"2401.14069","title":"Neural Sinkhorn Gradient Flow","created":"2024-01-25","cited_by_count":9,"area":null},{"id":"2410.12000","title":"Parametric model reduction of mean-field and stochastic systems via higher-order action matching","created":"2024-10-15","cited_by_count":9,"area":null},{"id":"2411.18463","title":"Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension","created":"2024-11-26","cited_by_count":9,"area":null},{"id":"2503.11347","title":"Integrating Dynamical Systems Modeling with Spatiotemporal scRNA-seq Data Analysis","created":"2025-03-14","cited_by_count":9,"area":null},{"id":"2506.01502","title":"Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme","created":"2025-06-02","cited_by_count":9,"area":null},{"id":"2506.08902","title":"Intention-Conditioned Flow Occupancy Models","created":"2025-06-10","cited_by_count":9,"area":null},{"id":"2601.10061","title":"CoF-T2I: Video Models as Pure Visual Reasoners for Text-to-Image Generation","created":"2026-01-15","cited_by_count":9,"area":null},{"id":"2609.11801","title":"Thinking with Looped Flows","created":"2026-09-10","cited_by_count":9,"area":null},{"id":"2305.11857","title":"Computing high-dimensional optimal transport by flow neural networks","created":"2023-05-19","cited_by_count":8,"area":null},{"id":"2408.11686","title":"Plug-in estimation of Schr\\\"odinger bridges","created":"2024-08-21","cited_by_count":8,"area":null},{"id":"2410.15815","title":"Solvation Free Energies from Neural Thermodynamic Integration","created":"2024-10-21","cited_by_count":8,"area":null},{"id":"2412.03312","title":"Path-Guided Particle-based Sampling","created":"2024-12-04","cited_by_count":8,"area":null}],"next_cursor":"100"}