{"total":52,"rows":[{"id":"2003.00638","title":"Permutation Invariant Graph Generation via Score-Based Generative Modeling","created":"2020-03-02","cited_by_count":270,"area":"diffusion"},{"id":"2305.20009","title":"Protein Design with Guided Discrete Diffusion","created":"2023-05-31","cited_by_count":157,"area":"diffusion"},{"id":"2210.05274","title":"Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design","created":"2022-10-11","cited_by_count":122,"area":"diffusion"},{"id":"2405.11416","title":"Discrete-state Continuous-time Diffusion for Graph Generation","created":"2024-05-19","cited_by_count":76,"area":"diffusion"},{"id":"2209.05710","title":"MDM: Molecular Diffusion Model for 3D Molecule Generation","created":"2022-09-13","cited_by_count":58,"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":"2402.16359","title":"Feedback Efficient Online Fine-Tuning of Diffusion Models","created":"2024-02-26","cited_by_count":53,"area":"diffusion"},{"id":"2304.01565","title":"A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material","created":"2023-04-04","cited_by_count":35,"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":"2502.12638","title":"NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation","created":"2025-02-18","cited_by_count":17,"area":"diffusion"},{"id":"2301.10250","title":"Solving Inverse Physics Problems with Score Matching","created":"2023-01-24","cited_by_count":16,"area":"diffusion"},{"id":"2508.17815","title":"Multi-domain Distribution Learning for De Novo Drug Design","created":"2025-08-25","cited_by_count":15,"area":"diffusion"},{"id":"2404.00569","title":"CM-TTS: Enhancing Real Time Text-to-Speech Synthesis Efficiency through Weighted Samplers and Consistency Models","created":"2024-03-31","cited_by_count":13,"area":"diffusion"},{"id":"2502.16824","title":"Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization","created":"2025-02-24","cited_by_count":13,"area":"diffusion"},{"id":"2405.17829","title":"LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative Latent Space Surpasses AR Models","created":"2024-05-28","cited_by_count":11,"area":"diffusion"},{"id":"2407.11942","title":"Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design","created":"2024-07-16","cited_by_count":11,"area":"diffusion"},{"id":"2502.06027","title":"Generating 3D Binding Molecules Using Shape-Conditioned Diffusion Models with Guidance","created":"2025-02-09","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":"2406.10513","title":"Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space","created":"2024-06-15","cited_by_count":8,"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":"2410.06502","title":"Chemistry-Inspired Diffusion with Non-Differentiable Guidance","created":"2024-10-09","cited_by_count":6,"area":"diffusion"},{"id":"2310.04463","title":"Diffusing on Two Levels and Optimizing for Multiple Properties: A Novel Approach to Generating Molecules with Desirable Properties","created":"2023-10-05","cited_by_count":5,"area":"diffusion"},{"id":"2507.05024","title":"A Generative Diffusion Model for Amorphous Materials","created":"2025-07-07","cited_by_count":5,"area":"diffusion"},{"id":"2405.03799","title":"Synthetic Data from Diffusion Models Improve Drug Discovery Prediction","created":"2024-05-06","cited_by_count":4,"area":"diffusion"},{"id":"2508.16521","title":"Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation","created":"2025-08-22","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":"2604.16648","title":"FRIGID: Scaling Diffusion-Based Molecular Generation from Mass Spectra at Training and Inference Time","created":"2026-04-17","cited_by_count":4,"area":"diffusion"},{"id":"2408.09896","title":"Instruction-Based Molecular Graph Generation with Unified Text-Graph Diffusion Model","created":"2024-08-19","cited_by_count":3,"area":"diffusion"},{"id":"2510.21153","title":"Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design","created":"2025-10-24","cited_by_count":3,"area":"diffusion"},{"id":"2512.05844","title":"NEAT: Neighborhood-Guided, Efficient, Autoregressive Set Transformer for 3D Molecular Generation","created":"2025-12-05","cited_by_count":3,"area":"diffusion"},{"id":"2211.08506","title":"ParticleGrid: Enabling Deep Learning using 3D Representation of Materials","created":"2022-11-15","cited_by_count":2,"area":"diffusion"},{"id":"2411.09356","title":"Multi-scale Generative Modeling for Fast Sampling","created":"2024-11-14","cited_by_count":2,"area":"diffusion"},{"id":"2604.00236","title":"Hierarchical Discrete Flow Matching for Graph Generation","created":"2026-03-31","cited_by_count":2,"area":"diffusion"},{"id":"2504.06312","title":"DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform","created":"2025-04-08","cited_by_count":1,"area":"diffusion"},{"id":"2508.06364","title":"ActivityDiff: A diffusion model with Positive and Negative Activity Guidance for De Novo Drug Design","created":"2025-08-08","cited_by_count":1,"area":"diffusion"},{"id":"2605.10385","title":"Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputs","created":"2026-05-11","cited_by_count":1,"area":"diffusion"},{"id":"2605.25681","title":"Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models","created":"2026-05-25","cited_by_count":1,"area":"diffusion"},{"id":"2609.37875","title":"Co-PiLOT: Constrained Physics-Informed Latent Optimization for Target-Driven Inverse Design","created":"2026-09-29","cited_by_count":1,"area":"diffusion"},{"id":"2412.04242","title":"LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation","created":"2024-12-05","cited_by_count":0,"area":"diffusion"},{"id":"2504.20770","title":"JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation","created":"2025-04-29","cited_by_count":0,"area":"diffusion"},{"id":"2508.14748","title":"Cross-Modality Controlled Molecule Generation with Diffusion Language Model","created":"2025-08-20","cited_by_count":0,"area":"diffusion"},{"id":"2509.23800","title":"Sample-Efficient Optimisation over the Outputs of Generative Models","created":"2025-09-28","cited_by_count":0,"area":"diffusion"},{"id":"2509.25198","title":"SOLD: SELFIES-based Objective-driven Latent Diffusion","created":"2025-09-03","cited_by_count":0,"area":"diffusion"},{"id":"2604.03409","title":"Generative AI for material design: A mechanics perspective from burgers to matter","created":"2026-04-03","cited_by_count":0,"area":"diffusion"},{"id":"2605.09439","title":"Inverse Design for Conditional Distribution Matching","created":"2026-05-10","cited_by_count":0,"area":"diffusion"},{"id":"2605.20235","title":"Provably Learning Diffusion Models under the Manifold Hypothesis: Collapse and Refine","created":"2026-05-16","cited_by_count":0,"area":"diffusion"},{"id":"2605.26540","title":"Domain-Gated Latent Diffusion: Generative Inverse Design of HMX-Class Energetic Materials with First-Principles Validation","created":"2026-05-26","cited_by_count":0,"area":"diffusion"},{"id":"2605.28226","title":"PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion","created":"2026-05-27","cited_by_count":0,"area":"diffusion"},{"id":"2606.01461","title":"Genotype-Conditioned Molecular Generation via Evidence-Grounded Multi-Objective Latent Perturbation in Diffusion Models","created":"2026-05-31","cited_by_count":0,"area":"diffusion"},{"id":"2607.01105","title":"SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles","created":"2026-07-01","cited_by_count":0,"area":"diffusion"},{"id":"2607.21634","title":"MotifRole-Diff: Risk-Optimal Role-Aware Corruption for Masked Molecular Graph Diffusion","created":"2026-07-20","cited_by_count":0,"area":"diffusion"},{"id":"2610.15284","title":"FragFlex: Fragment-Based Flexible Molecular Generation for Exploring Vast Chemical Space","created":"2026-10-11","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}