{"total":78,"rows":[{"id":"2408.12528","title":"Show-o: One Single Transformer to Unify Multimodal Understanding and Generation","created":"2024-08-22","cited_by_count":752,"area":null},{"id":"2509.26328","title":"Fast-dLLM v2: Efficient Block-Diffusion LLM","created":"2025-09-30","cited_by_count":139,"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":"2302.03596","title":"Graph Generation with Diffusion Mixture","created":"2023-02-07","cited_by_count":55,"area":null},{"id":"2409.17808","title":"Generative Modeling of Molecular Dynamics Trajectories","created":"2024-09-26","cited_by_count":51,"area":null},{"id":"2507.18578","title":"Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs","created":"2025-07-24","cited_by_count":46,"area":null},{"id":"2506.10848","title":"Accelerating Diffusion Large Language Models with SlowFast Sampling: The Three Golden Principles","created":"2025-06-12","cited_by_count":45,"area":null},{"id":"2305.10690","title":"Sampling, Diffusions, and Stochastic Localization","created":"2023-05-18","cited_by_count":40,"area":null},{"id":"2512.03759","title":"Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective","created":"2025-12-03","cited_by_count":34,"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":"2604.09784","title":"Discrete Flow Maps","created":"2026-04-10","cited_by_count":29,"area":null},{"id":"2502.11420","title":"Training-Free Guidance Beyond Differentiability: Scalable Path Steering with Tree Search in Diffusion and Flow Models","created":"2025-02-17","cited_by_count":24,"area":null},{"id":"2305.18375","title":"Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling","created":"2023-05-28","cited_by_count":18,"area":null},{"id":"2410.18403","title":"Structure Language Models for Protein Conformation Generation","created":"2024-10-24","cited_by_count":17,"area":null},{"id":"2501.01073","title":"Graph Generative Pre-trained Transformer","created":"2025-01-02","cited_by_count":17,"area":null},{"id":"2507.15897","title":"ReDi: Rectified Discrete Flow","created":"2025-07-21","cited_by_count":14,"area":null},{"id":"2505.17741","title":"Discrete Neural Flow Samplers with Locally Equivariant Transformer","created":"2025-05-23","cited_by_count":13,"area":null},{"id":"2505.05755","title":"Insertion Language Models: Sequence Generation with Arbitrary-Position Insertions","created":"2025-05-09","cited_by_count":11,"area":null},{"id":"2602.07132","title":"Discrete Adjoint Matching","created":"2026-02-06","cited_by_count":11,"area":null},{"id":"2306.09099","title":"Unbalanced Diffusion Schr\\\"odinger Bridge","created":"2023-06-15","cited_by_count":9,"area":null},{"id":"2608.13520","title":"The data geometry of masking diffusion: Certified-optimal schedules via unmasking growth complexity","created":"2026-08-13","cited_by_count":9,"area":null},{"id":"2507.00425","title":"Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows","created":"2025-07-01","cited_by_count":8,"area":null},{"id":"2507.14156","title":"All-atom inverse protein folding through discrete flow matching","created":"2025-07-04","cited_by_count":8,"area":null},{"id":"2501.19040","title":"Towards the Worst-case Robustness of Large Language Models","created":"2025-01-31","cited_by_count":7,"area":null},{"id":"2509.21983","title":"Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning","created":"2025-09-26","cited_by_count":7,"area":null},{"id":"2512.07173","title":"Improving the Throughput of Diffusion-based Large Language Models via a Training-Free Confidence-Aware Calibration","created":"2025-12-08","cited_by_count":7,"area":null},{"id":"2605.10727","title":"Kernel-Gradient Drifting Models","created":"2026-05-11","cited_by_count":7,"area":null},{"id":"2606.08417","title":"Hacking Generative Perplexity: Why Unconditional Text Evaluation Needs Distributional Metrics","created":"2026-06-07","cited_by_count":7,"area":null},{"id":"2407.11954","title":"Gated Temporal Diffusion for Stochastic Long-Term Dense Anticipation","created":"2024-07-16","cited_by_count":6,"area":null},{"id":"2505.18883","title":"Partition Generative Modeling: Masked Modeling Without Masks","created":"2025-05-24","cited_by_count":6,"area":null},{"id":"2605.05629","title":"Spherical Flows for Sampling Categorical Data","created":"2026-05-07","cited_by_count":6,"area":null},{"id":"2412.01019","title":"Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces","created":"2024-12-02","cited_by_count":5,"area":null},{"id":"2505.08531","title":"Building-Block Aware Generative Modeling for 3D Crystals of Metal Organic Frameworks","created":"2025-05-13","cited_by_count":4,"area":null},{"id":"2602.08243","title":"Discrete Adjoint Schr\\\"odinger Bridge Sampler","created":"2026-02-09","cited_by_count":4,"area":null},{"id":"2604.08964","title":"Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models","created":"2026-04-10","cited_by_count":4,"area":null},{"id":"2505.22494","title":"ProSpero: Active Learning for Robust Protein Design Beyond Wild-Type Neighborhoods","created":"2025-05-28","cited_by_count":3,"area":null},{"id":"2506.16404","title":"Generating Directed Graphs with Dual Attention and Asymmetric Encoding","created":"2025-06-19","cited_by_count":3,"area":null},{"id":"2510.23106","title":"Sampling from Energy distributions with Target Concrete Score Identity","created":"2025-10-27","cited_by_count":3,"area":null},{"id":"2605.08044","title":"Fast Byte Latent Transformer","created":"2026-05-08","cited_by_count":3,"area":null},{"id":"2502.19183","title":"INFO-SEDD: Continuous Time Markov Chains as Scalable Information Metrics Estimators","created":"2025-02-26","cited_by_count":2,"area":null},{"id":"2510.09685","title":"Deep Neural Networks Inspired by Differential Equations","created":"2025-10-09","cited_by_count":2,"area":null},{"id":"2605.09291","title":"dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models","created":"2026-05-10","cited_by_count":2,"area":null},{"id":"2606.02955","title":"Fast-dLLM++: Fr\\'{e}chet Profile Decoding for Faster Diffusion LLM Inference","created":"2026-06-01","cited_by_count":2,"area":null},{"id":"2607.21636","title":"Measuring the Dependency Gap: Diagnosing Inter-Column Fidelity in Tabular Generative Models","created":"2026-07-20","cited_by_count":2,"area":null},{"id":"2303.02737","title":"SePaint: Semantic Map Inpainting via Multinomial Diffusion","created":"2023-03-05","cited_by_count":1,"area":null},{"id":"2412.08565","title":"GenPlan: Generative Sequence Models as Adaptive Planners","created":"2024-12-11","cited_by_count":1,"area":null},{"id":"2502.07616","title":"Tractable Transformers for Flexible Conditional Generation","created":"2025-02-11","cited_by_count":1,"area":null},{"id":"2509.01736","title":"Multimodal Generative Flows for LHC Jets","created":"2025-09-01","cited_by_count":1,"area":null},{"id":"2601.16249","title":"Ordering-based Causal Discovery via Generalized Score Matching","created":"2026-01-22","cited_by_count":1,"area":null},{"id":"2602.03496","title":"Lookahead Path Likelihood Optimization for Diffusion LLMs","created":"2026-02-03","cited_by_count":1,"area":null},{"id":"2602.08894","title":"Discrete Bridges for Mutual Information Estimation","created":"2026-02-09","cited_by_count":1,"area":null},{"id":"2605.16941","title":"Roll Out and Roll Back: Diffusion LLMs are Their Own Efficiency Teachers","created":"2026-05-16","cited_by_count":1,"area":null},{"id":"2607.13188","title":"Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes","created":"2026-07-14","cited_by_count":1,"area":null},{"id":"2609.23290","title":"Stochastic Flow Map for Count Data","created":"2026-09-20","cited_by_count":1,"area":null},{"id":"2410.02628","title":"Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization","created":"2024-10-03","cited_by_count":0,"area":null},{"id":"2410.21518","title":"Predicting sub-population specific viral evolution","created":"2024-10-28","cited_by_count":0,"area":null},{"id":"2509.23825","title":"Electric Currents for Discrete Data Generation","created":"2025-09-28","cited_by_count":0,"area":null},{"id":"2510.12916","title":"Efficient Inference for Coupled Hidden Markov Models in Continuous Time and Discrete Space","created":"2025-10-14","cited_by_count":0,"area":null},{"id":"2511.03113","title":"FP-AbDiff: Improving Score-based Antibody Design by Capturing Nonequilibrium Dynamics through the Underlying Fokker-Planck Equation","created":"2025-11-05","cited_by_count":0,"area":null},{"id":"2511.09433","title":"What We Don't C: Manifold Disentanglement for Structured Discovery","created":"2025-11-12","cited_by_count":0,"area":null},{"id":"2603.17353","title":"Learning Permutation Distributions via Reflected Diffusion on Ranks","created":"2026-03-18","cited_by_count":0,"area":null},{"id":"2605.09085","title":"Constant-Target Energy Matching: A Unified Framework for Continuous and Discrete Density Estimation","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2605.14716","title":"SCAMP: Sparse-anchor Control is One Small Projection","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2606.04974","title":"SAID: Accelerating Diffusion-Based Language Models via Scaffold-Aware Iterative Decoding","created":"2026-06-03","cited_by_count":0,"area":null},{"id":"2608.13457","title":"Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2608.28681","title":"CARD: Calibration via Agreement in Reverse Diffusion for Out-of-Domain MRI Segmentation","created":"2026-08-26","cited_by_count":0,"area":null},{"id":"2609.05801","title":"Evidence-Aligned Local Composition of Discrete Experts for Sequence Restoration","created":"2026-09-05","cited_by_count":0,"area":null},{"id":"2609.37043","title":"Iterative Exact Discrete Guidance for Energy-Based Sampling","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2609.38484","title":"RetroGEF: Dynamic Graph Edit Flow for Single-Step Retrosynthesis","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.01355","title":"Discrete Wasserstein Flows for One-Step Generative Modeling","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.01663","title":"pCoMole: Pareto-Constrained Molecule Editing with Discrete Flows","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.01739","title":"Fixed-point neural samplers on discrete spaces","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.05071","title":"Discrete Action Matching: Learning Stochastic Dynamics from Samples via State Graphs","created":"2026-10-04","cited_by_count":0,"area":null},{"id":"2610.10990","title":"Omni-Diffusion-Distill: Few-Step Distillation of Unified Multimodal Diffusion Large Language Models","created":"2026-10-07","cited_by_count":0,"area":null},{"id":"2610.12545","title":"AutoIndexer: Flexible-Order Decoding by Training Causal Models on Chains of Edits","created":"2026-10-08","cited_by_count":0,"area":null},{"id":"2610.13225","title":"ReSFlow: Rectifying Categorical Flows on Statistical Manifolds for One-Step Generation","created":"2026-10-09","cited_by_count":0,"area":null},{"id":"2610.19053","title":"Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes","created":"2026-10-13","cited_by_count":0,"area":null},{"id":"2610.19946","title":"Learning Graph Energies for Finite-Time Generation","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}