{"total":135,"rows":[{"id":"2508.10875","title":"A Survey on Diffusion Language Models","created":"2025-08-14","cited_by_count":78,"area":"diffusion"},{"id":"2605.10938","title":"ELF: Embedded Language Flows","created":"2026-05-11","cited_by_count":45,"area":"diffusion"},{"id":"2602.12233","title":"Categorical Flow Maps","created":"2026-02-12","cited_by_count":44,"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":"2601.07568","title":"d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation","created":"2026-01-12","cited_by_count":37,"area":"inference"},{"id":"2604.11748","title":"LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling","created":"2026-04-13","cited_by_count":36,"area":"diffusion"},{"id":"2512.10858","title":"Scaling Behavior of Discrete Diffusion Language Models","created":"2025-12-11","cited_by_count":35,"area":"diffusion"},{"id":"2510.01329","title":"Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling","created":"2025-10-01","cited_by_count":34,"area":"diffusion"},{"id":"2510.22510","title":"CANDI: Hybrid Discrete-Continuous Diffusion Models","created":"2025-10-26","cited_by_count":34,"area":"diffusion"},{"id":"2512.14067","title":"Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed","created":"2025-12-16","cited_by_count":33,"area":"diffusion"},{"id":"2510.03206","title":"Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner","created":"2025-10-03","cited_by_count":32,"area":"lr"},{"id":"2508.08712","title":"A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models","created":"2025-08-12","cited_by_count":30,"area":"diffusion"},{"id":"2509.21474","title":"d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation","created":"2025-09-25","cited_by_count":27,"area":"lr"},{"id":"2602.15014","title":"Scaling Beyond Masked Diffusion Language Models","created":"2026-02-16","cited_by_count":27,"area":"diffusion"},{"id":"2607.05722","title":"Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decoding","created":"2026-07-07","cited_by_count":24,"area":null},{"id":"2510.02212","title":"DiFFPO: Training Diffusion LLMs to Reason Fast and Furious via Reinforcement Learning","created":"2025-10-02","cited_by_count":19,"area":"lr"},{"id":"2605.18530","title":"Continuous Diffusion Scales Competitively with Discrete Diffusion for Language","created":"2026-05-18","cited_by_count":19,"area":"diffusion"},{"id":"2604.08302","title":"DMax: Aggressive Parallel Decoding for dLLMs","created":"2026-04-09","cited_by_count":18,"area":"diffusion"},{"id":"2509.25035","title":"Ultra-Fast Language Generation via Discrete Diffusion Divergence Instruct","created":"2025-09-29","cited_by_count":16,"area":"diffusion"},{"id":"2510.17206","title":"Soft-Masked Diffusion Language Models","created":"2025-10-20","cited_by_count":16,"area":"diffusion"},{"id":"2604.02718","title":"Generative Frontiers: Why Evaluation Matters for Diffusion Language Models","created":"2026-04-03","cited_by_count":16,"area":"diffusion"},{"id":"2507.15897","title":"ReDi: Rectified Discrete Flow","created":"2025-07-21","cited_by_count":14,"area":null},{"id":"2605.06548","title":"Continuous Latent Diffusion Language Model","created":"2026-05-07","cited_by_count":14,"area":"diffusion"},{"id":"2607.00714","title":"Self-conditioned Flow Map Language Models via Fixed-point Flows","created":"2026-07-01","cited_by_count":14,"area":null},{"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":"2602.21185","title":"The Diffusion Duality, Chapter II: $\\Psi$-Samplers","created":"2026-02-24","cited_by_count":12,"area":"diffusion"},{"id":"2603.20155","title":"Beyond Single Tokens: Distilling Discrete Diffusion Models via Discrete MMD","created":"2026-03-20","cited_by_count":12,"area":"diffusion"},{"id":"2508.04884","title":"The Cosine Schedule is Fisher-Rao-Optimal for Masked Discrete Diffusion Models","created":"2025-08-06","cited_by_count":11,"area":"diffusion"},{"id":"2512.02892","title":"Fast-Decoding Diffusion Language Models via Progress-Aware Confidence Schedules","created":"2025-12-02","cited_by_count":11,"area":"diffusion"},{"id":"2605.07933","title":"How to Train Your Latent Diffusion Language Model Jointly With the Latent Space","created":"2026-05-08","cited_by_count":11,"area":"diffusion"},{"id":"2509.24368","title":"Watermarking Diffusion Language Models","created":"2025-09-29","cited_by_count":10,"area":"diffusion"},{"id":"2510.08632","title":"Next Semantic Scale Prediction via Hierarchical Diffusion Language Models","created":"2025-10-08","cited_by_count":8,"area":"diffusion"},{"id":"2510.19304","title":"Loopholing Discrete Diffusion: Deterministic Bypass of the Sampling Wall","created":"2025-10-22","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":"2605.07820","title":"Scaling Categorical Flow Maps","created":"2026-05-08","cited_by_count":8,"area":"diffusion"},{"id":"2509.19707","title":"Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies","created":"2025-09-24","cited_by_count":7,"area":null},{"id":"2602.01705","title":"LaDi-RL: Latent Diffusion Reasoning Prevents Entropy Collapse in Reinforcement Learning","created":"2026-02-02","cited_by_count":7,"area":"lr"},{"id":"2602.01842","title":"Prism: Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models","created":"2026-02-02","cited_by_count":7,"area":"lr"},{"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":"2509.22925","title":"Soft-Di[M]O: Improving One-Step Discrete Image Generation with Soft Embeddings","created":"2025-09-26","cited_by_count":6,"area":"diffusion"},{"id":"2509.26364","title":"Data-to-Energy Stochastic Dynamics","created":"2025-09-30","cited_by_count":6,"area":"diffusion"},{"id":"2511.15927","title":"DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone","created":"2025-11-19","cited_by_count":6,"area":"diffusion"},{"id":"2602.02112","title":"Unifying Masked Diffusion Models with Various Generation Orders and Beyond","created":"2026-02-02","cited_by_count":6,"area":"diffusion"},{"id":"2605.05629","title":"Spherical Flows for Sampling Categorical Data","created":"2026-05-07","cited_by_count":6,"area":null},{"id":"2606.01774","title":"FLARE: Diffusion for Hybrid Language Model","created":"2026-06-01","cited_by_count":6,"area":null},{"id":"2512.20063","title":"PairFlow: Closed-Form Source-Target Coupling for Few-Step Generation in Discrete Flow Models","created":"2025-12-23","cited_by_count":5,"area":null},{"id":"2604.00375","title":"Locally Confident, Globally Stuck: The Quality-Exploration Dilemma in Diffusion Language Models","created":"2026-04-01","cited_by_count":5,"area":"lr"},{"id":"2605.31215","title":"Fixed-Point Masked Generative Modeling","created":"2026-05-29","cited_by_count":5,"area":"inference"},{"id":"2608.02602","title":"AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling","created":"2026-08-03","cited_by_count":5,"area":"diffusion"},{"id":"2510.09477","title":"Efficient Autoregressive Inference for Transformer Probabilistic Models","created":"2025-10-10","cited_by_count":4,"area":null},{"id":"2601.16971","title":"Auto-Regressive Masked Diffusion Models","created":"2026-01-23","cited_by_count":4,"area":"diffusion"},{"id":"2605.23605","title":"DiLaDiff: Distilled Latent-Augmented Diffusion for Language Modeling","created":"2026-05-22","cited_by_count":4,"area":"diffusion"},{"id":"2605.31314","title":"AR Forcing: Towards Long-Horizon Robot Navigation World Model","created":"2026-05-29","cited_by_count":4,"area":"wm"},{"id":"2607.00773","title":"Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling","created":"2026-07-01","cited_by_count":4,"area":"diffusion"},{"id":"2510.27480","title":"Simplex-to-Euclidean Bijections for Categorical Flow Matching","created":"2025-10-31","cited_by_count":3,"area":"diffusion"},{"id":"2602.01362","title":"Balancing Understanding and Generation in Discrete Diffusion Models","created":"2026-02-01","cited_by_count":3,"area":"diffusion"},{"id":"2602.16169","title":"Discrete Stochastic Localization for Non-autoregressive Generation","created":"2026-02-18","cited_by_count":3,"area":"diffusion"},{"id":"2603.21342","title":"Generalized Discrete Diffusion from Snapshots","created":"2026-03-22","cited_by_count":3,"area":"diffusion"},{"id":"2604.05497","title":"Thinking Diffusion: Penalize and Guide Visual-Grounded Reasoning in Diffusion Multimodal Language Models","created":"2026-04-07","cited_by_count":3,"area":"lr"},{"id":"2605.00182","title":"Towards A Generative Protein Evolution Machine with DPLM-Evo","created":"2026-04-30","cited_by_count":3,"area":"diffusion"},{"id":"2509.05056","title":"Masked Diffusion Language Models with Frequency-Informed Training","created":"2025-09-05","cited_by_count":2,"area":"diffusion"},{"id":"2510.22926","title":"Simple Denoising Diffusion Language Models","created":"2025-10-27","cited_by_count":2,"area":"diffusion"},{"id":"2510.26200","title":"Don't Let It Fade: Preserving Edits in Diffusion Language Models via Token Timestep Allocation","created":"2025-10-30","cited_by_count":2,"area":"diffusion"},{"id":"2512.05092","title":"Foundations of Diffusion Models in General State Spaces: A Self-Contained Introduction","created":"2025-12-04","cited_by_count":2,"area":"diffusion"},{"id":"2604.03779","title":"CountsDiff: A Diffusion Model on the Natural Numbers for Generation and Imputation of Count-Based Data","created":"2026-04-04","cited_by_count":2,"area":"diffusion"},{"id":"2605.07193","title":"Coupling Models for One-Step Discrete Generation","created":"2026-05-08","cited_by_count":2,"area":null},{"id":"2605.07971","title":"DVD: Discrete Voxel Diffusion for 3D Generation and Editing","created":"2026-05-08","cited_by_count":2,"area":"diffusion"},{"id":"2605.19470","title":"Drifting Objectives for Refining Discrete Diffusion Language Models","created":"2026-05-19","cited_by_count":2,"area":"diffusion"},{"id":"2606.19475","title":"Diffusion Language Models: An Experimental Analysis","created":"2026-06-17","cited_by_count":2,"area":"diffusion"},{"id":"2607.01775","title":"Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding","created":"2026-07-02","cited_by_count":2,"area":"diffusion"},{"id":"2608.10615","title":"Simplex Relaxation for Discrete Diffusion","created":"2026-08-11","cited_by_count":2,"area":"diffusion"},{"id":"2608.23551","title":"ConvergeFlow: Language Flow with Provable Convergence to Token Embeddings","created":"2026-08-24","cited_by_count":2,"area":"diffusion"},{"id":"2609.04010","title":"Unlocking Lossless Speedups in LLMs via Discrete Diffusion","created":"2026-09-03","cited_by_count":2,"area":"diffusion"},{"id":"2609.11998","title":"Fixed State, Long Reach: What a Constant-Size Cache Buys Block Diffusion at Scale","created":"2026-09-09","cited_by_count":2,"area":"diffusion"},{"id":"2509.20896","title":"Deterministic Discrete Denoising","created":"2025-09-25","cited_by_count":1,"area":"diffusion"},{"id":"2512.15923","title":"A Unification of Discrete, Gaussian, and Simplicial Diffusion","created":"2025-12-17","cited_by_count":1,"area":"diffusion"},{"id":"2605.09820","title":"Dystruct: Dynamically Structured Diffusion Language Model Decoding via Bayesian Inference","created":"2026-05-10","cited_by_count":1,"area":"diffusion"},{"id":"2605.10518","title":"Infinite Mask Diffusion for Few-Step Distillation","created":"2026-05-11","cited_by_count":1,"area":"diffusion"},{"id":"2605.26106","title":"Looped Diffusion Language Models","created":"2026-05-25","cited_by_count":1,"area":"diffusion"},{"id":"2606.08810","title":"Continuous Language Diffusion as a Decoder-Interface Problem","created":"2026-06-07","cited_by_count":1,"area":"diffusion"},{"id":"2606.17999","title":"VoidPadding: Let [VOID] Handle Padding in Masked Diffusion Language Models so that [EOS] Can Focus on Semantic Termination","created":"2026-06-16","cited_by_count":1,"area":"diffusion"},{"id":"2607.14106","title":"Token Time Continuous Diffusion for Language Modeling","created":"2026-05-07","cited_by_count":1,"area":"diffusion"},{"id":"2607.17884","title":"ST-Veto: Spatio-Temporal Token Veto for Diffusion MLLMs via Taylor Prediction and Visual Grounding","created":"2026-07-20","cited_by_count":1,"area":"lr"},{"id":"2607.19686","title":"Multi-Mask Diffusion Language Models for Few-Step Generation","created":"2026-07-22","cited_by_count":1,"area":"diffusion"},{"id":"2607.21585","title":"Expanding Flow Maps","created":"2026-07-23","cited_by_count":1,"area":null},{"id":"2607.26504","title":"From Interface to Inference: Eliciting Any-Order Inference from Any-Order Models","created":"2026-07-29","cited_by_count":1,"area":"diffusion"},{"id":"2608.07594","title":"Scaling Inherently Interpretable Language Models","created":"2026-08-06","cited_by_count":1,"area":"diffusion"},{"id":"2608.13925","title":"CForce: Boosting Parallel Decoding for dLLMs via Consistency Forcing","created":"2026-08-14","cited_by_count":1,"area":"inference"},{"id":"2609.01043","title":"From Truncation to Commitment: Persistent Context in Uniform Discrete Diffusion","created":"2026-09-01","cited_by_count":1,"area":"diffusion"},{"id":"2609.29102","title":"ELF-REG: Scaling Continuous Diffusion Language Models to Reasoning Tasks","created":"2026-09-24","cited_by_count":1,"area":"lr"},{"id":"2601.02799","title":"Stratified Hazard Sampling: Minimal-Variance Event Scheduling for CTMC/DTMC Discrete Diffusion and Flow Models","created":"2026-01-06","cited_by_count":0,"area":"diffusion"},{"id":"2602.00792","title":"Latent Shadows: The Gaussian-Discrete Duality in Masked Diffusion","created":"2026-01-31","cited_by_count":0,"area":"diffusion"},{"id":"2604.14001","title":"Diffusion Language Models for Speech Recognition","created":"2026-04-15","cited_by_count":0,"area":"diffusion"},{"id":"2604.17310","title":"Interpolating Discrete Diffusion Models with Controllable Resampling","created":"2026-04-19","cited_by_count":0,"area":"diffusion"},{"id":"2604.26841","title":"Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data","created":"2026-04-29","cited_by_count":0,"area":"diffusion"},{"id":"2605.07924","title":"Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation","created":"2026-05-08","cited_by_count":0,"area":"diffusion"},{"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":"2605.09302","title":"Discrete Langevin-Inspired Posterior Sampling","created":"2026-05-10","cited_by_count":0,"area":"diffusion"},{"id":"2605.12836","title":"Discrete Stochastic Localization for Non-autoregressive Generation","created":"2026-05-13","cited_by_count":0,"area":"diffusion"},{"id":"2605.13026","title":"Understanding and Accelerating the Training of Masked Diffusion Language Models","created":"2026-05-13","cited_by_count":0,"area":"diffusion"}],"next_cursor":"100"}