{"total":339,"rows":[{"id":"2502.00816","title":"Sundial: A Family of Highly Capable Time Series Foundation Models","created":"2025-02-02","cited_by_count":180,"area":null},{"id":"2412.15322","title":"MMAudio: Taming Multimodal Joint Training for High-Quality Video-to-Audio Synthesis","created":"2024-12-19","cited_by_count":134,"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":"2310.00429","title":"On the Stability of Iterative Retraining of Generative Models on their own Data","created":"2023-09-30","cited_by_count":100,"area":null},{"id":"2310.03725","title":"Stochastic interpolants with data-dependent couplings","created":"2023-10-05","cited_by_count":100,"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":"2412.07081","title":"Sequential Controlled Langevin Diffusions","created":"2024-12-10","cited_by_count":48,"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":"2406.07266","title":"SemlaFlow -- Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matching","created":"2024-06-11","cited_by_count":41,"area":null},{"id":"2310.02233","title":"Generalized Schr\\\"odinger Bridge Matching","created":"2023-10-03","cited_by_count":40,"area":null},{"id":"2502.18462","title":"Scalable Equilibrium Sampling with Sequential Boltzmann Generators","created":"2025-02-25","cited_by_count":38,"area":null},{"id":"2308.10364","title":"SE(3) Equivariant Augmented Coupling Flows","created":"2023-08-20","cited_by_count":37,"area":null},{"id":"2607.08639","title":"Native Video-Action Pretraining for Generalizable Robot Control","created":"2026-07-09","cited_by_count":36,"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":"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":"2404.04240","title":"Dynamic Conditional Optimal Transport through Simulation-Free Flows","created":"2024-04-05","cited_by_count":25,"area":null},{"id":"2405.06672","title":"Liouville Flow Importance Sampler","created":"2024-05-03","cited_by_count":25,"area":null},{"id":"2503.09817","title":"Temporal Difference Flows","created":"2025-03-12","cited_by_count":24,"area":null},{"id":"2402.05443","title":"Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport","created":"2024-02-08","cited_by_count":23,"area":null},{"id":"2406.12616","title":"Learning diffusion at lightspeed","created":"2024-06-18","cited_by_count":22,"area":null},{"id":"2407.07873","title":"Dynamical Measure Transport and Neural PDE Solvers for Sampling","created":"2024-07-10","cited_by_count":20,"area":null},{"id":"2603.09936","title":"Generative Drifting is Secretly Score Matching: a Spectral and Variational Perspective","created":"2026-03-10","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":"2310.03695","title":"Multimarginal generative modeling with stochastic interpolants","created":"2023-10-05","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":"2502.12456","title":"Not-So-Optimal Transport Flows for 3D Point Cloud Generation","created":"2025-02-18","cited_by_count":17,"area":null},{"id":"2504.07894","title":"DiverseFlow: Sample-Efficient Diverse Mode Coverage in Flows","created":"2025-04-10","cited_by_count":17,"area":null},{"id":"2504.11516","title":"FEAT: Free energy Estimators with Adaptive Transport","created":"2025-04-15","cited_by_count":16,"area":null},{"id":"2409.10966","title":"CUNSB-RFIE: Context-aware Unpaired Neural Schr\\\"odinger Bridge in Retinal Fundus Image Enhancement","created":"2024-09-17","cited_by_count":13,"area":null},{"id":"2410.12779","title":"Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds","created":"2024-10-16","cited_by_count":13,"area":null},{"id":"2412.01383","title":"Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data","created":"2024-12-02","cited_by_count":13,"area":null},{"id":"2502.02300","title":"Density Ratio Estimation with Conditional Probability Paths","created":"2025-02-04","cited_by_count":13,"area":null},{"id":"2505.18392","title":"Applications of Modular Co-Design for De Novo 3D Molecule Generation","created":"2025-05-23","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":"2310.01105","title":"Energy-Guided Continuous Entropic Barycenter Estimation for General Costs","created":"2023-10-02","cited_by_count":12,"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":"2505.11197","title":"Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schr\\\"odinger Bridge","created":"2025-05-16","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":"2505.05034","title":"Dequantified Diffusion-Schr{\\\"o}dinger Bridge for Density Ratio Estimation","created":"2025-05-08","cited_by_count":11,"area":null},{"id":"2505.11823","title":"Variational Regularized Unbalanced Optimal Transport: Single Network, Least Action","created":"2025-05-17","cited_by_count":11,"area":null},{"id":"2505.18817","title":"High-order Equivariant Flow Matching for Density Functional Theory Hamiltonian Prediction","created":"2025-05-24","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":"2506.10168","title":"Momentum Multi-Marginal Schr\\\"odinger Bridge Matching","created":"2025-06-11","cited_by_count":11,"area":null},{"id":"2506.16656","title":"Mesh-Informed Neural Operator : A Transformer Generative Approach","created":"2025-06-20","cited_by_count":11,"area":null},{"id":"2507.15833","title":"Look, Focus, Act: Efficient and Robust Robot Learning via Human Gaze and Foveated Vision Transformers","created":"2025-07-21","cited_by_count":11,"area":null},{"id":"2405.19679","title":"Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging","created":"2024-05-30","cited_by_count":10,"area":null},{"id":"2406.05061","title":"Progressive Entropic Optimal Transport Solvers","created":"2024-06-07","cited_by_count":10,"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":"2505.19972","title":"PHI: Bridging Domain Shift in Long-Term Action Quality Assessment via Progressive Hierarchical Instruction","created":"2025-05-26","cited_by_count":10,"area":null},{"id":"2401.14069","title":"Neural Sinkhorn Gradient Flow","created":"2024-01-25","cited_by_count":9,"area":null},{"id":"2407.10703","title":"Towards Robust Event-based Networks for Nighttime via Unpaired Day-to-Night Event Translation","created":"2024-07-15","cited_by_count":9,"area":null},{"id":"2410.03974","title":"Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport","created":"2024-10-04","cited_by_count":9,"area":null},{"id":"2410.07501","title":"Inferring biological processes with intrinsic noise from cross-sectional data","created":"2024-10-10","cited_by_count":9,"area":null},{"id":"2503.03025","title":"Hierarchical Refinement: Optimal Transport to Infinity and Beyond","created":"2025-03-04","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":"2602.07098","title":"BayesFlow 2: Multi-Backend Amortized Bayesian Inference in Python","created":"2026-02-06","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":"2311.05788","title":"Structured Transforms Across Spaces with Cost-Regularized Optimal Transport","created":"2023-11-09","cited_by_count":8,"area":null},{"id":"2409.16681","title":"Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions","created":"2024-09-25","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":"2412.10966","title":"FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Prediction","created":"2024-12-14","cited_by_count":8,"area":null},{"id":"2502.09655","title":"Bidirectional Diffusion Bridge Models","created":"2025-02-12","cited_by_count":8,"area":null},{"id":"2503.24322","title":"NoProp: Training Neural Networks without Full Back-propagation or Full Forward-propagation","created":"2025-03-31","cited_by_count":8,"area":null},{"id":"2508.13479","title":"AIM 2025 challenge on Inverse Tone Mapping Report: Methods and Results","created":"2025-08-19","cited_by_count":8,"area":null},{"id":"2510.05849","title":"ESS-Flow: Training-free guidance of flow-based models as inference in source space","created":"2025-10-07","cited_by_count":8,"area":null},{"id":"2305.19303","title":"MAGNet: Motif-Agnostic Generation of Molecules from Shapes","created":"2023-05-30","cited_by_count":7,"area":null},{"id":"2410.20622","title":"Kernel Approximation of Fisher-Rao Gradient Flows","created":"2024-10-27","cited_by_count":7,"area":null},{"id":"2411.05238","title":"Generating Highly Designable Proteins with Geometric Algebra Flow Matching","created":"2024-11-07","cited_by_count":7,"area":null},{"id":"2505.22049","title":"Differentiable Generalized Sliced Wasserstein Plans","created":"2025-05-28","cited_by_count":7,"area":null},{"id":"2507.00846","title":"BoltzNCE: Learning Likelihoods for Boltzmann Generation with Stochastic Interpolants and Noise Contrastive Estimation","created":"2025-07-01","cited_by_count":7,"area":null},{"id":"2510.15038","title":"AlignFlow: Improving Flow-based Generative Models with Semi-Discrete Optimal Transport","created":"2025-10-16","cited_by_count":7,"area":null},{"id":"2511.00977","title":"Modeling Microenvironment Trajectories on Spatial Transcriptomics with NicheFlow","created":"2025-11-02","cited_by_count":7,"area":null},{"id":"2601.01568","title":"MM-Sonate: Multimodal Controllable Audio-Video Generation with Zero-Shot Voice Cloning","created":"2026-01-04","cited_by_count":7,"area":null},{"id":"2502.04583","title":"Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plan","created":"2025-02-07","cited_by_count":6,"area":null},{"id":"2509.01486","title":"Prior-Guided Flow Matching for Target-Aware Molecule Design with Learnable Atom Number","created":"2025-09-01","cited_by_count":6,"area":null},{"id":"2509.24779","title":"MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models","created":"2025-09-29","cited_by_count":6,"area":null},{"id":"2510.08294","title":"Counterfactual Identifiability via Dynamic Optimal Transport","created":"2025-10-09","cited_by_count":6,"area":null},{"id":"2512.16607","title":"Boltzmann generators for amorphous particle systems","created":"2025-12-18","cited_by_count":6,"area":null},{"id":"2406.13661","title":"Hitchhiker's guide on the relation of Energy-Based Models with other generative models, sampling and statistical physics: a comprehensive review","created":"2024-06-19","cited_by_count":5,"area":null},{"id":"2408.16046","title":"Scaling Up Diffusion and Flow-based XGBoost Models","created":"2024-08-28","cited_by_count":5,"area":null},{"id":"2410.02656","title":"Scalable Simulation-free Entropic Unbalanced Optimal Transport","created":"2024-10-03","cited_by_count":5,"area":null},{"id":"2412.10743","title":"NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models","created":"2024-12-14","cited_by_count":5,"area":null},{"id":"2505.06549","title":"Good Things Come in Pairs: Paired Autoencoders for Inverse Problems","created":"2025-05-10","cited_by_count":5,"area":null},{"id":"2505.16082","title":"Oh SnapMMD! Forecasting Stochastic Dynamics Beyond the Schr\\\"odinger Bridge's End","created":"2025-05-21","cited_by_count":5,"area":null},{"id":"2506.09007","title":"Branched Schr\\\"odinger Bridge Matching","created":"2025-06-10","cited_by_count":5,"area":null},{"id":"2507.00480","title":"Posterior Inference in Latent Space for Scalable Constrained Black-box Optimization","created":"2025-07-01","cited_by_count":5,"area":null},{"id":"2507.11789","title":"Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation","created":"2025-07-15","cited_by_count":5,"area":null},{"id":"2507.11818","title":"SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling","created":"2025-07-16","cited_by_count":5,"area":null},{"id":"2509.22138","title":"Slicing Wasserstein Over Wasserstein Via Functional Optimal Transport","created":"2025-09-26","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":"2510.21542","title":"HollowFlow: Efficient Sample Likelihood Evaluation using Hollow Message Passing","created":"2025-10-24","cited_by_count":5,"area":null},{"id":"2602.22251","title":"Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials","created":"2026-02-24","cited_by_count":5,"area":null},{"id":"2605.08550","title":"A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots","created":"2026-05-08","cited_by_count":5,"area":null},{"id":"2410.07550","title":"Conditional Lagrangian Wasserstein Flow for Time Series Imputation","created":"2024-10-10","cited_by_count":4,"area":null}],"next_cursor":"100"}