{"list":"other","total":59,"rows":[{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"2011.13456","title":"Score-Based Generative Modeling through Stochastic Differential Equations","created":"2020-11-26","cited_by_count":9122},{"id":"2212.09748","title":"Scalable Diffusion Models with Transformers","created":"2022-12-19","cited_by_count":6054},{"id":"2012.12877","title":"Training data-efficient image transformers & distillation through attention","created":"2020-12-23","cited_by_count":4586},{"id":"1806.07366","title":"Neural Ordinary Differential Equations","created":"2018-06-19","cited_by_count":3779},{"id":"2310.16834","title":"Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution","created":"2023-10-25","cited_by_count":745},{"id":"2401.08740","title":"SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers","created":"2024-01-16","cited_by_count":737},{"id":"2106.01357","title":"Diffusion Schr\\\"odinger Bridge with Applications to Score-Based Generative Modeling","created":"2021-06-01","cited_by_count":602},{"id":"2205.14987","title":"A Continuous Time Framework for Discrete Denoising Models","created":"2022-05-30","cited_by_count":451},{"id":"2406.03736","title":"Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data","created":"2024-06-06","cited_by_count":381},{"id":"1308.0215","title":"A survey of the Schr\\\"odinger problem and some of its connections with optimal transport","created":"2013-08-01","cited_by_count":292},{"id":"2001.01328","title":"Scalable Gradients for Stochastic Differential Equations","created":"2020-01-05","cited_by_count":271},{"id":"2403.13298","title":"Rotary Position Embedding for Vision Transformer","created":"2024-03-20","cited_by_count":236},{"id":"2409.08861","title":"Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control","created":"2024-09-13","cited_by_count":233},{"id":"2110.11291","title":"Likelihood Training of Schr\\\"odinger Bridge using Forward-Backward SDEs Theory","created":"2021-10-21","cited_by_count":219},{"id":"2111.15141","title":"Path Integral Sampler: a stochastic control approach for sampling","created":"2021-11-30","cited_by_count":181},{"id":"2412.10193","title":"Simple Guidance Mechanisms for Discrete Diffusion Models","created":"2024-12-13","cited_by_count":155},{"id":"2302.13834","title":"Denoising Diffusion Samplers","created":"2023-02-27","cited_by_count":149},{"id":"2307.01198","title":"Improved sampling via learned diffusions","created":"2023-07-03","cited_by_count":104},{"id":"1412.4430","title":"On the relation between optimal transport and Schr\\\"odinger bridges: A stochastic control viewpoint","created":"2014-12-15","cited_by_count":99},{"id":"2504.11713","title":"Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching","created":"2025-04-16","cited_by_count":85},{"id":"2410.02711","title":"NETS: A Non-Equilibrium Transport Sampler","created":"2024-10-03","cited_by_count":69},{"id":"2402.06320","title":"Particle Denoising Diffusion Sampler","created":"2024-02-09","cited_by_count":65},{"id":"2406.01661","title":"A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization","created":"2024-06-03","cited_by_count":59},{"id":"1611.07422","title":"Deep Learning Approximation for Stochastic Control Problems","created":"2016-11-02","cited_by_count":55},{"id":"2402.08667","title":"Target Score Matching","created":"2024-02-13","cited_by_count":50},{"id":"2410.03601","title":"How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework","created":"2024-10-04","cited_by_count":48},{"id":"2412.07081","title":"Sequential Controlled Langevin Diffusions","created":"2024-12-10","cited_by_count":48},{"id":"2502.00234","title":"Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms","created":"2025-02-01","cited_by_count":47},{"id":"2402.08095","title":"Convergence Analysis of Discrete Diffusion Model: Exact Implementation through Uniformization","created":"2024-02-12","cited_by_count":44},{"id":"2312.02027","title":"Stochastic Optimal Control Matching","created":"2023-12-04","cited_by_count":40},{"id":"1506.04255","title":"Entropic and displacement interpolation: a computational approach using the Hilbert metric","created":"2015-06-13","cited_by_count":34},{"id":"2502.10843","title":"LEAPS: A discrete neural sampler via locally equivariant networks","created":"2025-02-15","cited_by_count":31},{"id":"2502.08696","title":"Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics","created":"2025-02-12","cited_by_count":29},{"id":"2503.01006","title":"Underdamped Diffusion Bridges with Applications to Sampling","created":"2025-03-02","cited_by_count":29},{"id":"2502.06685","title":"No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers","created":"2025-02-10","cited_by_count":28},{"id":"2506.16471","title":"Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities","created":"2025-06-19","cited_by_count":26},{"id":"2504.16431","title":"Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion","created":"2025-04-23","cited_by_count":25},{"id":"2311.14156","title":"Variational Annealing on Graphs for Combinatorial Optimization","created":"2023-11-23","cited_by_count":21},{"id":"2410.01500","title":"Discrete Diffusion Schr\\\"odinger Bridge Matching for Graph Transformation","created":"2024-10-02","cited_by_count":21},{"id":"2508.10684","title":"MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control","created":"2025-08-14","cited_by_count":21},{"id":"2510.08233","title":"Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization","created":"2025-10-09","cited_by_count":20},{"id":"2502.10328","title":"Accelerated Parallel Tempering via Neural Transports","created":"2025-02-14","cited_by_count":17},{"id":"2405.20630","title":"Stochastic Optimal Control for Diffusion Bridges in Function Spaces","created":"2024-05-31","cited_by_count":16},{"id":"2504.11516","title":"FEAT: Free energy Estimators with Adaptive Transport","created":"2025-04-15","cited_by_count":16},{"id":"2510.03824","title":"Proximal Diffusion Neural Sampler","created":"2025-10-04","cited_by_count":16},{"id":"2504.03461","title":"Conditioning Diffusions Using Malliavin Calculus","created":"2025-04-04","cited_by_count":15},{"id":"2512.05116","title":"Value Gradient Guidance for Flow Matching Alignment","created":"2025-12-04","cited_by_count":14},{"id":"2505.17741","title":"Discrete Neural Flow Samplers with Locally Equivariant Transformer","created":"2025-05-23","cited_by_count":13},{"id":"2506.05231","title":"Progressive Tempering Sampler with Diffusion","created":"2025-06-05","cited_by_count":13},{"id":"2602.07132","title":"Discrete Adjoint Matching","created":"2026-02-06","cited_by_count":11},{"id":"2405.03549","title":"Bridging discrete and continuous state spaces: Exploring the Ehrenfest process in time-continuous diffusion models","created":"2024-05-06","cited_by_count":8},{"id":"2506.18165","title":"Non-equilibrium Annealed Adjoint Sampler","created":"2025-06-22","cited_by_count":8},{"id":"2506.10982","title":"Rethinking Losses for Diffusion Bridge Samplers","created":"2025-06-12","cited_by_count":7},{"id":"2512.05070","title":"Control Consistency Losses for Diffusion Bridges","created":"2025-12-04","cited_by_count":6},{"id":"2512.20003","title":"Control Variate Score Matching for Diffusion Models","created":"2025-12-23","cited_by_count":6},{"id":"2511.06239","title":"Functional Adjoint Sampler: Scalable Sampling on Infinite Dimensional Spaces","created":"2025-11-09","cited_by_count":4},{"id":"2505.19646","title":"Energy-based generator matching: A neural sampler for general state space","created":"2025-05-26","cited_by_count":3},{"id":"2510.23106","title":"Sampling from Energy distributions with Target Concrete Score Identity","created":"2025-10-27","cited_by_count":3}],"next_cursor":null}