{"total":66,"rows":[{"id":"2205.14217","title":"Diffusion-LM Improves Controllable Text Generation","created":"2022-05-27","cited_by_count":1027,"area":null},{"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":"2406.01572","title":"Unlocking Guidance for Discrete State-Space Diffusion and Flow Models","created":"2024-06-03","cited_by_count":129,"area":null},{"id":"2312.06647","title":"4M: Massively Multimodal Masked Modeling","created":"2023-12-11","cited_by_count":120,"area":null},{"id":"2202.06533","title":"An Introduction to Neural Data Compression","created":"2022-02-14","cited_by_count":79,"area":null},{"id":"2204.09269","title":"A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond","created":"2022-04-20","cited_by_count":64,"area":null},{"id":"2205.13554","title":"Training and Inference on Any-Order Autoregressive Models the Right Way","created":"2022-05-26","cited_by_count":64,"area":null},{"id":"2304.06632","title":"AI-Generated Content (AIGC): A Survey","created":"2023-03-26","cited_by_count":59,"area":null},{"id":"2409.17808","title":"Generative Modeling of Molecular Dynamics Trajectories","created":"2024-09-26","cited_by_count":51,"area":null},{"id":"2202.03528","title":"TACTiS: Transformer-Attentional Copulas for Time Series","created":"2022-02-07","cited_by_count":38,"area":null},{"id":"2506.01928","title":"Esoteric Language Models: A Family of Any-Order Diffusion LLMs","created":"2025-06-02","cited_by_count":34,"area":null},{"id":"2303.14468","title":"Autoregressive Conditional Neural Processes","created":"2023-03-25","cited_by_count":33,"area":null},{"id":"2503.05979","title":"Learning-Order Autoregressive Models with Application to Molecular Graph Generation","created":"2025-03-07","cited_by_count":29,"area":null},{"id":"2509.04185","title":"Set Block Decoding is a Language Model Inference Accelerator","created":"2025-09-04","cited_by_count":23,"area":null},{"id":"2501.01073","title":"Graph Generative Pre-trained Transformer","created":"2025-01-02","cited_by_count":17,"area":null},{"id":"2406.00758","title":"Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaptation","created":"2024-06-02","cited_by_count":16,"area":null},{"id":"2503.04641","title":"Simulating the Real World: A Unified Survey of Multimodal Generative Models","created":"2025-03-06","cited_by_count":15,"area":null},{"id":"2409.10847","title":"BAD: Bidirectional Auto-regressive Diffusion for Text-to-Motion Generation","created":"2024-09-17","cited_by_count":13,"area":null},{"id":"2410.02143","title":"Plug-and-Play Controllable Generation for Discrete Masked Models","created":"2024-10-03","cited_by_count":11,"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":"2205.14568","title":"Towards Instance-Wise Calibration: Local Amortized Diagnostics and Reshaping of Conditional Densities (LADaR)","created":"2022-05-29","cited_by_count":10,"area":null},{"id":"2411.02120","title":"Bridge-IF: Learning Inverse Protein Folding with Markov Bridges","created":"2024-11-04","cited_by_count":9,"area":null},{"id":"2305.14651","title":"Revisit and Outstrip Entity Alignment: A Perspective of Generative Models","created":"2023-05-24","cited_by_count":8,"area":null},{"id":"2402.10516","title":"Generative AI for Controllable Protein Sequence Design: A Survey","created":"2024-02-16","cited_by_count":8,"area":null},{"id":"2410.21299","title":"TV-3DG: Mastering Text-to-3D Customized Generation with Visual Prompt","created":"2024-10-16","cited_by_count":8,"area":null},{"id":"2502.06901","title":"Enabling Autoregressive Models to Fill In Masked Tokens","created":"2025-02-09","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":"2305.12144","title":"DiffCap: Exploring Continuous Diffusion on Image Captioning","created":"2023-05-20","cited_by_count":5,"area":null},{"id":"2310.09685","title":"Generative artificial intelligence for de novo protein design","created":"2023-10-15","cited_by_count":5,"area":null},{"id":"2310.12920","title":"Generative Marginalization Models","created":"2023-10-19","cited_by_count":5,"area":null},{"id":"2407.05593","title":"Unmasking Trees for Tabular Data","created":"2024-07-08","cited_by_count":4,"area":null},{"id":"2510.09477","title":"Efficient Autoregressive Inference for Transformer Probabilistic Models","created":"2025-10-10","cited_by_count":4,"area":null},{"id":"2603.11703","title":"EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering","created":"2026-03-12","cited_by_count":4,"area":null},{"id":"2207.03887","title":"Generative Adversarial Networks and Other Generative Models","created":"2022-07-08","cited_by_count":3,"area":null},{"id":"2408.04461","title":"Random Walk Diffusion for Efficient Large-Scale Graph Generation","created":"2024-08-08","cited_by_count":3,"area":null},{"id":"2410.09675","title":"COrAL: Order-Agnostic Language Modeling for Efficient Iterative Refinement","created":"2024-10-12","cited_by_count":3,"area":null},{"id":"2412.04737","title":"Generative Humanization for Therapeutic Antibodies","created":"2024-12-06","cited_by_count":3,"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":"2508.17345","title":"ShortListing Model: A Streamlined SimplexDiffusion for Discrete Variable Generation","created":"2025-08-24","cited_by_count":3,"area":null},{"id":"2405.14221","title":"Survey on Visual Signal Coding and Processing with Generative Models: Technologies, Standards and Optimization","created":"2024-05-23","cited_by_count":2,"area":null},{"id":"2410.01820","title":"PixelBytes: Catching Unified Representation for Multimodal Generation","created":"2024-09-16","cited_by_count":2,"area":null},{"id":"2411.19182","title":"SOWing Information: Cultivating Contextual Coherence with MLLMs in Image Generation","created":"2024-11-28","cited_by_count":2,"area":null},{"id":"2502.09587","title":"Rolling Ahead Diffusion for Traffic Scene Simulation","created":"2025-02-13","cited_by_count":2,"area":null},{"id":"2506.17983","title":"LVPNet: A Latent-variable-based Prediction-driven End-to-end Framework for Lossless Compression of Medical Images","created":"2025-06-22","cited_by_count":2,"area":null},{"id":"2603.10302","title":"How to make the most of your masked language model for protein engineering","created":"2026-03-11","cited_by_count":2,"area":null},{"id":"2605.07193","title":"Coupling Models for One-Step Discrete Generation","created":"2026-05-08","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":"2210.10715","title":"Autoregressive Generative Modeling with Noise Conditional Maximum Likelihood Estimation","created":"2022-10-19","cited_by_count":1,"area":null},{"id":"2411.06608","title":"MolMiner: Toward Controllable, 3D-Aware, Fragment-Based Molecular Design","created":"2024-11-10","cited_by_count":1,"area":null},{"id":"2503.19274","title":"CoMAC: Conversational Agent for Multi-Source Auxiliary Context with Sparse and Symmetric Latent Interactions","created":"2025-03-25","cited_by_count":1,"area":null},{"id":"2504.17069","title":"Distilling Specialized Orders for Visual Generation","created":"2025-04-23","cited_by_count":1,"area":null},{"id":"2505.11610","title":"Foundation Models for AI-Enabled Biological Design","created":"2025-05-16","cited_by_count":1,"area":null},{"id":"2505.20827","title":"Frame-Level Captions for Long Video Generation with Complex Multi Scenes","created":"2025-05-27","cited_by_count":1,"area":null},{"id":"2605.26285","title":"Two-Parameter Flows for Learning Population Dynamics of Physical Systems","created":"2026-05-25","cited_by_count":1,"area":null},{"id":"2605.29194","title":"Stochastic Lifting for Generating Trajectories of Stochastic Physical Systems","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2206.12351","title":"Megapixel Image Generation with Step-Unrolled Denoising Autoencoders","created":"2022-06-24","cited_by_count":0,"area":null},{"id":"2408.16553","title":"Downscaling Neural Network for Coastal Simulations","created":"2024-08-29","cited_by_count":0,"area":null},{"id":"2409.10978","title":"Edge-based Denoising Image Compression","created":"2024-09-17","cited_by_count":0,"area":null},{"id":"2507.02670","title":"Guided Generation for Developable Antibodies","created":"2025-07-03","cited_by_count":0,"area":null},{"id":"2512.20724","title":"SA-DiffuSeq: Addressing Computational and Scalability Challenges in Long-Document Generation with Sparse Attention","created":"2025-12-23","cited_by_count":0,"area":null},{"id":"2605.06355","title":"Order-Agnostic Autoregressive Modelling with Missing Data","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2606.12609","title":"Viral Proteins Reveal Geometry of Protein Language Models","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2606.21097","title":"GRAG: Generic Response-Augmented Generation Framework for Personalized Conversational Systems","created":"2026-06-19","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":"2610.01739","title":"Fixed-point neural samplers on discrete spaces","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.10440","title":"Seq-Flow: Efficient Probabilistic Forecasting with Self-Rollout Error Control","created":"2026-10-07","cited_by_count":0,"area":null}],"next_cursor":null}