{"total":169,"rows":[{"id":"2406.07524","title":"Simple and Effective Masked Diffusion Language Models","created":"2024-06-11","cited_by_count":848,"area":"diffusion"},{"id":"2406.04329","title":"Simplified and Generalized Masked Diffusion for Discrete Data","created":"2024-06-06","cited_by_count":626,"area":"diffusion"},{"id":"2407.15595","title":"Discrete Flow Matching","created":"2024-07-22","cited_by_count":317,"area":"diffusion"},{"id":"2412.10193","title":"Simple Guidance Mechanisms for Discrete Diffusion Models","created":"2024-12-13","cited_by_count":155,"area":"diffusion"},{"id":"2408.08252","title":"Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding","created":"2024-08-15","cited_by_count":136,"area":"diffusion"},{"id":"2505.24857","title":"Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking","created":"2025-05-30","cited_by_count":131,"area":"diffusion"},{"id":"2407.02398","title":"Consistency Flow Matching: Defining Straight Flows with Velocity Consistency","created":"2024-07-02","cited_by_count":104,"area":"diffusion"},{"id":"2407.13734","title":"Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review","created":"2024-07-18","cited_by_count":98,"area":"diffusion"},{"id":"2410.21357","title":"Energy-Based Diffusion Language Models for Text Generation","created":"2024-10-28","cited_by_count":89,"area":"diffusion"},{"id":"2501.09685","title":"Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review","created":"2025-01-16","cited_by_count":88,"area":"diffusion"},{"id":"2406.04843","title":"Variational Flow Matching for Graph Generation","created":"2024-06-07","cited_by_count":83,"area":"diffusion"},{"id":"2502.03540","title":"Path Planning for Masked Diffusion Model Sampling","created":"2025-02-05","cited_by_count":80,"area":"diffusion"},{"id":"2410.13643","title":"Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design","created":"2024-10-17","cited_by_count":79,"area":"diffusion"},{"id":"2503.03965","title":"All-atom Diffusion Transformers: Unified generative modelling of molecules and materials","created":"2025-03-05","cited_by_count":75,"area":"diffusion"},{"id":"2405.14664","title":"Fisher Flow Matching for Generative Modeling over Discrete Data","created":"2024-05-23","cited_by_count":72,"area":"diffusion"},{"id":"2412.03487","title":"Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective","created":"2024-12-04","cited_by_count":57,"area":"diffusion"},{"id":"2506.09018","title":"Edit Flows: Flow Matching with Edit Operations","created":"2025-06-10","cited_by_count":55,"area":"diffusion"},{"id":"2404.19739","title":"Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation","created":"2024-04-30","cited_by_count":54,"area":"diffusion"},{"id":"2509.01025","title":"Any-Order Flexible Length Masked Diffusion","created":"2025-08-31","cited_by_count":51,"area":"diffusion"},{"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,"area":"diffusion"},{"id":"2405.16441","title":"Categorical Flow Matching on Statistical Manifolds","created":"2024-05-26","cited_by_count":47,"area":"diffusion"},{"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,"area":"diffusion"},{"id":"2502.09622","title":"Theoretical Benefit and Limitation of Diffusion Language Model","created":"2025-02-13","cited_by_count":47,"area":"diffusion"},{"id":"2602.12233","title":"Categorical Flow Maps","created":"2026-02-12","cited_by_count":44,"area":"diffusion"},{"id":"2408.14608","title":"Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold","created":"2024-08-26","cited_by_count":43,"area":"diffusion"},{"id":"2405.15986","title":"Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity","created":"2024-05-24","cited_by_count":42,"area":"diffusion"},{"id":"2510.09541","title":"SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models","created":"2025-10-10","cited_by_count":41,"area":"diffusion"},{"id":"2410.07761","title":"$\\textit{Jump Your Steps}$: Optimizing Sampling Schedule of Discrete Diffusion Models","created":"2024-10-10","cited_by_count":40,"area":"diffusion"},{"id":"2510.01384","title":"Fine-Tuning Masked Diffusion for Provable Self-Correction","created":"2025-10-01","cited_by_count":39,"area":"diffusion"},{"id":"2405.20313","title":"Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation","created":"2024-05-30","cited_by_count":36,"area":"diffusion"},{"id":"2412.17762","title":"The Superposition of Diffusion Models Using the It\\^o Density Estimator","created":"2024-12-23","cited_by_count":36,"area":"diffusion"},{"id":"2506.02070","title":"An Introduction to Flow Matching and Diffusion Models","created":"2025-06-02","cited_by_count":35,"area":"diffusion"},{"id":"2410.08134","title":"Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction","created":"2024-10-10","cited_by_count":32,"area":"diffusion"},{"id":"2502.06079","title":"Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo","created":"2025-02-10","cited_by_count":31,"area":"diffusion"},{"id":"2502.02582","title":"Open Materials Generation with Stochastic Interpolants","created":"2025-02-04","cited_by_count":28,"area":"diffusion"},{"id":"2405.19673","title":"Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models","created":"2024-05-30","cited_by_count":25,"area":"diffusion"},{"id":"2504.16431","title":"Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion","created":"2025-04-23","cited_by_count":25,"area":"diffusion"},{"id":"2410.02321","title":"Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis","created":"2024-10-03","cited_by_count":24,"area":"diffusion"},{"id":"2505.21400","title":"Breaking AR's Sampling Bottleneck: Provable Acceleration via Diffusion Language Models","created":"2025-05-27","cited_by_count":23,"area":"diffusion"},{"id":"2411.07506","title":"FlowTS: Time Series Generation via Rectified Flow","created":"2024-11-12","cited_by_count":22,"area":"diffusion"},{"id":"2506.07903","title":"Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces","created":"2025-06-09","cited_by_count":21,"area":"diffusion"},{"id":"2508.12629","title":"FlowMol3: Flow Matching for 3D De Novo Small-Molecule Generation","created":"2025-08-18","cited_by_count":21,"area":"diffusion"},{"id":"2509.16756","title":"Discrete Diffusion Models: Novel Analysis and New Sampler Guarantees","created":"2025-09-20","cited_by_count":20,"area":"diffusion"},{"id":"2605.18530","title":"Continuous Diffusion Scales Competitively with Discrete Diffusion for Language","created":"2026-05-18","cited_by_count":19,"area":"diffusion"},{"id":"2504.10283","title":"$\\alpha$-Flow: A Unified Framework for Continuous-State Discrete Flow Matching Models","created":"2025-04-14","cited_by_count":18,"area":"diffusion"},{"id":"2506.05668","title":"RNE: plug-and-play diffusion inference-time control and energy-based training","created":"2025-06-06","cited_by_count":17,"area":"diffusion"},{"id":"2509.20624","title":"FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Models","created":"2025-09-24","cited_by_count":17,"area":"diffusion"},{"id":"2509.18480","title":"SimpleFold: Folding Proteins is Simpler than You Think","created":"2025-09-23","cited_by_count":16,"area":"diffusion"},{"id":"2506.08316","title":"Why Masking Diffusion Works: Condition on the Jump Schedule for Improved Discrete Diffusion","created":"2025-06-10","cited_by_count":15,"area":"diffusion"},{"id":"2507.17731","title":"Flow Matching Meets Biology and Life Science: A Survey","created":"2025-07-23","cited_by_count":14,"area":"diffusion"},{"id":"2509.22623","title":"A Theoretical Analysis of Discrete Flow Matching Generative Models","created":"2025-09-26","cited_by_count":14,"area":"diffusion"},{"id":"2509.23405","title":"Planner Aware Path Learning in Diffusion Language Models Training","created":"2025-09-27","cited_by_count":14,"area":"diffusion"},{"id":"2503.07197","title":"Effective and Efficient Masked Image Generation Models","created":"2025-03-10","cited_by_count":13,"area":"diffusion"},{"id":"2503.08295","title":"Preference-Based Alignment of Discrete Diffusion Models","created":"2025-03-11","cited_by_count":13,"area":"diffusion"},{"id":"2507.08980","title":"Learning Diffusion Models with Flexible Representation Guidance","created":"2025-07-11","cited_by_count":13,"area":"diffusion"},{"id":"2605.22765","title":"Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation","created":"2026-05-21","cited_by_count":13,"area":"diffusion"},{"id":"2507.04832","title":"Discrete Diffusion Trajectory Alignment via Stepwise Decomposition","created":"2025-07-07","cited_by_count":12,"area":"diffusion"},{"id":"2602.21185","title":"The Diffusion Duality, Chapter II: $\\Psi$-Samplers","created":"2026-02-24","cited_by_count":12,"area":"diffusion"},{"id":"2403.03726","title":"Diffusion on language model encodings for protein sequence generation","created":"2024-03-06","cited_by_count":11,"area":"diffusion"},{"id":"2405.17035","title":"Glauber Generative Model: Discrete Diffusion Models via Binary Classification","created":"2024-05-27","cited_by_count":11,"area":"diffusion"},{"id":"2411.16644","title":"Exploring Discrete Flow Matching for 3D De Novo Molecule Generation","created":"2024-11-25","cited_by_count":11,"area":"diffusion"},{"id":"2412.06787","title":"[MASK] is All You Need","created":"2024-12-09","cited_by_count":11,"area":"diffusion"},{"id":"2502.00500","title":"Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation","created":"2025-02-01","cited_by_count":11,"area":"diffusion"},{"id":"2503.17361","title":"Gumbel-Softmax Flow Matching with Straight-Through Guidance for Controllable Biological Sequence Generation","created":"2025-03-21","cited_by_count":11,"area":"diffusion"},{"id":"2411.05676","title":"Improving Molecular Graph Generation with Flow Matching and Optimal Transport","created":"2024-11-08","cited_by_count":10,"area":"diffusion"},{"id":"2503.21592","title":"Simple and Critical Iterative Denoising: A Recasting of Discrete Diffusion in Graph Generation","created":"2025-03-27","cited_by_count":10,"area":"diffusion"},{"id":"2602.00286","title":"Generation Order and Parallel Decoding in Masked Diffusion Models: An Information-Theoretic Perspective","created":"2026-01-30","cited_by_count":10,"area":"diffusion"},{"id":"2506.14020","title":"Bures-Wasserstein Flow Matching for Graph Generation","created":"2025-06-16","cited_by_count":9,"area":"diffusion"},{"id":"2506.18340","title":"Controlled Generation with Equivariant Variational Flow Matching","created":"2025-06-23","cited_by_count":9,"area":"diffusion"},{"id":"2509.21906","title":"Error Analysis of Discrete Flow with Generator Matching","created":"2025-09-26","cited_by_count":9,"area":"diffusion"},{"id":"2410.07430","title":"EventFlow: Forecasting Temporal Point Processes with Flow Matching","created":"2024-10-09","cited_by_count":8,"area":"diffusion"},{"id":"2502.07303","title":"Flow Matching for Collaborative Filtering","created":"2025-02-11","cited_by_count":8,"area":"diffusion"},{"id":"2509.19962","title":"Learnable Sampler Distillation for Discrete Diffusion Models","created":"2025-09-24","cited_by_count":8,"area":"diffusion"},{"id":"2510.06050","title":"Edit-Based Flow Matching for Temporal Point Processes","created":"2025-10-07","cited_by_count":8,"area":"diffusion"},{"id":"2602.19066","title":"IDLM: Inverse-distilled Diffusion Language Models","created":"2026-02-22","cited_by_count":8,"area":"diffusion"},{"id":"2502.15805","title":"FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching","created":"2025-02-19","cited_by_count":7,"area":"diffusion"},{"id":"2505.15093","title":"Steering Generative Models with Experimental Data for Protein Fitness Optimization","created":"2025-05-21","cited_by_count":7,"area":"diffusion"},{"id":"2504.08051","title":"Compositional Flows for 3D Molecule and Synthesis Pathway Co-design","created":"2025-04-10","cited_by_count":6,"area":"diffusion"},{"id":"2506.04439","title":"RETRO SYNFLOW: Discrete Flow Matching for Accurate and Diverse Single-Step Retrosynthesis","created":"2025-06-04","cited_by_count":6,"area":"diffusion"},{"id":"2509.21912","title":"Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching","created":"2025-09-26","cited_by_count":6,"area":"diffusion"},{"id":"2602.06138","title":"Flow Matching for Offline Reinforcement Learning with Discrete Actions","created":"2026-02-05","cited_by_count":6,"area":"diffusion"},{"id":"2404.12314","title":"Guided Discrete Diffusion for Electronic Health Record Generation","created":"2024-04-18","cited_by_count":5,"area":"diffusion"},{"id":"2411.00759","title":"Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching","created":"2024-11-01","cited_by_count":5,"area":"diffusion"},{"id":"2412.12540","title":"Stiefel Flow Matching for Moment-Constrained Structure Elucidation","created":"2024-12-17","cited_by_count":5,"area":"diffusion"},{"id":"2501.14216","title":"TFG-Flow: Training-free Guidance in Multimodal Generative Flow","created":"2025-01-24","cited_by_count":5,"area":"diffusion"},{"id":"2503.15457","title":"Di$\\mathtt{[M]}$O: Distilling Masked Diffusion Models into One-step Generator","created":"2025-03-19","cited_by_count":5,"area":"diffusion"},{"id":"2510.08369","title":"Guided Star-Shaped Masked Diffusion","created":"2025-10-09","cited_by_count":5,"area":"diffusion"},{"id":"2502.07939","title":"Bit-Level Discrete Diffusion with Markov Probabilistic Models: An Improved Framework with Sharp Convergence Bounds under Minimal Assumptions","created":"2025-02-11","cited_by_count":4,"area":"diffusion"},{"id":"2504.20754","title":"DDPS: Discrete Diffusion Posterior Sampling for Paths in Layered Graphs","created":"2025-04-29","cited_by_count":4,"area":"diffusion"},{"id":"2508.18949","title":"Energy-Based Flow Matching for Generating 3D Molecular Structure","created":"2025-08-26","cited_by_count":4,"area":"diffusion"},{"id":"2512.12198","title":"MolGuidance: Advanced Guidance Strategies for Conditional Molecular Generation with Flow Matching","created":"2025-12-13","cited_by_count":4,"area":"diffusion"},{"id":"2601.22107","title":"Prior-Informed Flow Matching for Graph Reconstruction","created":"2026-01-29","cited_by_count":4,"area":"diffusion"},{"id":"2602.10420","title":"Prediction--Loss Alignment for Sampler--Robust Flow Matching Training","created":"2026-02-11","cited_by_count":4,"area":"diffusion"},{"id":"2602.19980","title":"Discrete Diffusion Models Exploit Asymmetry to Solve Lookahead Planning Tasks","created":"2026-02-23","cited_by_count":4,"area":"diffusion"},{"id":"2603.04730","title":"Count Bridges enable Modeling and Deconvolving Transcriptomic Data","created":"2026-03-05","cited_by_count":4,"area":"diffusion"},{"id":"2503.19371","title":"Flow to Learn: Flow Matching on Neural Network Parameters","created":"2025-03-25","cited_by_count":3,"area":"diffusion"},{"id":"2509.26063","title":"Fading to Grow: Growing Preference Ratios via Preference Fading Discrete Diffusion for Recommendation","created":"2025-09-30","cited_by_count":3,"area":"diffusion"},{"id":"2510.04162","title":"Drax: Speech Recognition with Discrete Flow Matching","created":"2025-10-05","cited_by_count":3,"area":"diffusion"},{"id":"2510.10634","title":"ProteinAE: Protein Diffusion Autoencoders for Structure Encoding","created":"2025-10-12","cited_by_count":3,"area":"diffusion"},{"id":"2510.27480","title":"Simplex-to-Euclidean Bijections for Categorical Flow Matching","created":"2025-10-31","cited_by_count":3,"area":"diffusion"}],"next_cursor":"100"}