{"total":22,"rows":[{"id":"2406.07266","title":"SemlaFlow -- Efficient 3D Molecular Generation with Latent Attention and Equivariant Flow Matching","created":"2024-06-11","cited_by_count":41,"area":null},{"id":"2507.00899","title":"TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Quality","created":"2025-07-01","cited_by_count":12,"area":null},{"id":"2505.00169","title":"GEOM-Drugs Revisited: Toward More Chemically Accurate Benchmarks for 3D Molecule Generation","created":"2025-04-30","cited_by_count":8,"area":null},{"id":"2602.16796","title":"Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning","created":"2026-02-18","cited_by_count":8,"area":null},{"id":"2507.00846","title":"BoltzNCE: Learning Likelihoods for Boltzmann Generation with Stochastic Interpolants and Noise Contrastive Estimation","created":"2025-07-01","cited_by_count":7,"area":null},{"id":"2506.19865","title":"Scalable and Cost-Efficient de Novo Template-Based Molecular Generation","created":"2025-06-10","cited_by_count":5,"area":null},{"id":"2507.11818","title":"SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling","created":"2025-07-16","cited_by_count":5,"area":null},{"id":"2602.16020","title":"MolCrystalFlow: Molecular Crystal Structure Prediction via Flow Matching","created":"2026-02-17","cited_by_count":5,"area":null},{"id":"2601.16955","title":"3D Molecule Generation from Rigid Motifs via SE(3) Flows","created":"2026-01-23","cited_by_count":3,"area":null},{"id":"2605.30610","title":"Constrained Flow Optimization via Sequential Fine Tuning for Molecular Design","created":"2026-05-28","cited_by_count":3,"area":null},{"id":"2606.08802","title":"Active Flow Expansion for Out-of-Distribution Discovery: from Theory to Molecules","created":"2026-06-07","cited_by_count":3,"area":null},{"id":"2607.19519","title":"Boltzmann-Expected Molecular Design with Decoupled Annealing Flows","created":"2026-07-21","cited_by_count":2,"area":null},{"id":"2603.26889","title":"Property-Guided Molecular Generation and Optimization via Latent Flows","created":"2026-03-27","cited_by_count":1,"area":null},{"id":"2605.07693","title":"Toward Better Geometric Representations for Molecule Generative Models","created":"2026-05-08","cited_by_count":1,"area":null},{"id":"2607.09039","title":"Variable-Length Generative Protein Design via Generalized Poisson Flow","created":"2026-07-10","cited_by_count":1,"area":null},{"id":"2412.11439","title":"Sampling Out-of-Distribution Chemical Spaces via Bayesian Flow","created":"2024-12-16","cited_by_count":0,"area":null},{"id":"2506.01467","title":"Feature-Aware (Hyper)graph Generation via Next-Scale Prediction","created":"2025-06-02","cited_by_count":0,"area":null},{"id":"2605.18381","title":"Generating Physically Consistent Molecules with Energy-Based Models","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2605.31498","title":"Scalable Inference-Time Annealing with Surrogate Likelihood Estimators","created":"2026-05-29","cited_by_count":0,"area":null},{"id":"2609.05328","title":"Embedded Graph Flows for Categorical Graph Generation","created":"2026-09-04","cited_by_count":0,"area":null},{"id":"2609.10099","title":"A Systematic Evaluation of Molecule Generation Models for De Novo Drug Design: From Benchmarks to Practical Insights","created":"2026-09-09","cited_by_count":0,"area":null},{"id":"2609.40030","title":"Fenchel Tilting: Weighted Correction for Efficient Finetuning of Generative Models","created":"2026-09-30","cited_by_count":0,"area":null}],"next_cursor":null}