{"total":75,"rows":[{"id":"2512.04562","title":"LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative Models","created":"2025-12-04","cited_by_count":23,"area":null},{"id":"2508.12629","title":"FlowMol3: Flow Matching for 3D De Novo Small-Molecule Generation","created":"2025-08-18","cited_by_count":21,"area":"diffusion"},{"id":"2511.07158","title":"Guiding Generative Models to Uncover Diverse and Novel Crystals via Reinforcement Learning","created":"2025-11-10","cited_by_count":21,"area":"deeprl"},{"id":"2509.18480","title":"SimpleFold: Folding Proteins is Simpler than You Think","created":"2025-09-23","cited_by_count":16,"area":"diffusion"},{"id":"2509.07150","title":"PLaID++: A Preference Aligned Language Model for Targeted Inorganic Materials Design","created":"2025-09-08","cited_by_count":14,"area":"alignment"},{"id":"2510.23040","title":"LLM Meets Diffusion: A Hybrid Framework for Crystal Material Generation","created":"2025-10-27","cited_by_count":13,"area":"diffusion"},{"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":"2509.12178","title":"All that structure matches does not glitter","created":"2025-09-15","cited_by_count":12,"area":null},{"id":"2503.15567","title":"Towards Unified and Lossless Latent Space for 3D Molecular Latent Diffusion Modeling","created":"2025-03-19","cited_by_count":11,"area":"diffusion"},{"id":"2505.16379","title":"Materials Generation in the Era of Artificial Intelligence: A Comprehensive Survey","created":"2025-05-22","cited_by_count":10,"area":null},{"id":"2505.17914","title":"Flexible MOF Generation with Torsion-Aware Flow Matching","created":"2025-05-23","cited_by_count":10,"area":null},{"id":"2510.03511","title":"Platonic Transformers: A Solid Choice For Equivariance","created":"2025-10-03","cited_by_count":10,"area":null},{"id":"2604.02270","title":"Crystalite: A Lightweight Transformer for Efficient Crystal Modeling","created":"2026-04-02","cited_by_count":10,"area":null},{"id":"2505.13791","title":"Scalable Autoregressive 3D Molecule Generation","created":"2025-05-20","cited_by_count":8,"area":"diffusion"},{"id":"2602.00424","title":"Open Materials Generation with Inference-Time Reinforcement Learning","created":"2026-01-31","cited_by_count":8,"area":"deeprl"},{"id":"2509.23822","title":"Space Group Conditional Flow Matching","created":"2025-09-28","cited_by_count":7,"area":"diffusion"},{"id":"2510.02259","title":"Transformers Discover Molecular Structure Without Graph Priors","created":"2025-10-02","cited_by_count":7,"area":null},{"id":"2602.20210","title":"Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling","created":"2026-02-23","cited_by_count":7,"area":null},{"id":"2506.15378","title":"Sampling 3D Molecular Conformers with Diffusion Transformers","created":"2025-06-18","cited_by_count":6,"area":"diffusion"},{"id":"2507.04053","title":"TopoMAS: Large Language Model Driven Topological Materials Multiagent System","created":"2025-07-05","cited_by_count":6,"area":null},{"id":"2508.16614","title":"CrystalDiT: A Diffusion Transformer for Crystal Generation","created":"2025-08-13","cited_by_count":6,"area":"diffusion"},{"id":"2510.12405","title":"Continuous SUN (Stable, Unique, and Novel) Metric for Generative Modeling of Inorganic Crystals","created":"2025-10-14","cited_by_count":6,"area":null},{"id":"2512.16607","title":"Boltzmann generators for amorphous particle systems","created":"2025-12-18","cited_by_count":6,"area":null},{"id":"2603.22283","title":"End-to-End Training for Unified Tokenization and Latent Denoising","created":"2026-03-23","cited_by_count":6,"area":"diffusion"},{"id":"2510.00027","title":"Learning Inter-Atomic Potentials without Explicit Equivariance","created":"2025-09-25","cited_by_count":5,"area":null},{"id":"2511.09465","title":"Branching Flows: Discrete, Continuous, and Manifold Flow Matching with Splits and Deletions","created":"2025-11-12","cited_by_count":5,"area":"diffusion"},{"id":"2512.01756","title":"Mofasa: A Step Change in Metal-Organic Framework Generation","created":"2025-12-01","cited_by_count":5,"area":null},{"id":"2602.22251","title":"Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials","created":"2026-02-24","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":"2511.14426","title":"MiAD: Mirage Atom Diffusion for De Novo Crystal Generation","created":"2025-11-18","cited_by_count":4,"area":"diffusion"},{"id":"2512.03127","title":"Atomic Diffusion Models for Small Molecule Structure Elucidation from NMR Spectra","created":"2025-12-02","cited_by_count":4,"area":"diffusion"},{"id":"2601.13780","title":"Principled Latent Diffusion for Graphs via Laplacian Autoencoders","created":"2026-01-20","cited_by_count":4,"area":"diffusion"},{"id":"2603.17196","title":"Self-Conditioned Denoising for Atomistic Representation Learning","created":"2026-03-17","cited_by_count":4,"area":null},{"id":"2605.14759","title":"Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement","created":"2026-05-14","cited_by_count":4,"area":null},{"id":"2506.10186","title":"Scalable Non-Equivariant 3D Molecule Generation via Rotational Alignment","created":"2025-06-11","cited_by_count":3,"area":"diffusion"},{"id":"2603.00180","title":"NNiT: Width-Agnostic Neural Network Generation with Structurally Aligned Weight Spaces","created":"2026-02-26","cited_by_count":3,"area":null},{"id":"2605.12784","title":"ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery","created":"2026-05-12","cited_by_count":3,"area":"agents"},{"id":"2605.14344","title":"CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation","created":"2026-05-14","cited_by_count":3,"area":"lr"},{"id":"2506.17064","title":"Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings","created":"2025-06-20","cited_by_count":2,"area":"diffusion"},{"id":"2510.04646","title":"Predictive Feature Caching for Training-free Acceleration of Molecular Geometry Generation","created":"2025-10-06","cited_by_count":2,"area":"diffusion"},{"id":"2511.02986","title":"Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models","created":"2025-11-04","cited_by_count":2,"area":"diffusion"},{"id":"2512.09514","title":"Transport Novelty Distance: A Distributional Metric for Evaluating Material Generative Models","created":"2025-12-10","cited_by_count":2,"area":null},{"id":"2606.07239","title":"Generative Molecular Morphing for Flexible-Size Design via Unbalanced Optimal Transport","created":"2026-06-05","cited_by_count":2,"area":null},{"id":"2509.21811","title":"Scaling Laws for Neural Material Models","created":"2025-09-26","cited_by_count":1,"area":null},{"id":"2512.03077","title":"Irresponsible AI: big tech's influence on AI research and associated impacts","created":"2025-11-27","cited_by_count":1,"area":null},{"id":"2512.10991","title":"MolSculpt: Sculpting 3D Molecular Geometries from Chemical Syntax","created":"2025-12-09","cited_by_count":1,"area":"diffusion"},{"id":"2601.19076","title":"C2NP: A Benchmark for Learning Scale-Dependent Geometric Invariances in 3D Materials Generation","created":"2026-01-27","cited_by_count":1,"area":null},{"id":"2602.00785","title":"World Models as an Intermediary between Agents and the Real World","created":"2026-01-31","cited_by_count":1,"area":"wm"},{"id":"2602.09309","title":"How Far Can You Grow? Characterizing the Extrapolation Frontier of Graph Generative Models for Materials Science","created":"2026-02-10","cited_by_count":1,"area":null},{"id":"2602.12045","title":"Fourier Transformers for Latent Crystallographic Diffusion and Generative Modeling","created":"2026-02-12","cited_by_count":1,"area":"diffusion"},{"id":"2605.14769","title":"Composable Crystals: Controllable Materials Discovery via Concept Learning","created":"2026-05-14","cited_by_count":1,"area":null},{"id":"2606.00776","title":"Latent Diffusion Pretraining for Crystal Property Prediction","created":"2026-05-30","cited_by_count":1,"area":"diffusion"},{"id":"2606.28578","title":"Surrogate-Gated Generation and Foundation-Model Embeddings for Bayesian Materials Design","created":"2026-06-26","cited_by_count":1,"area":null},{"id":"2607.09277","title":"Autoregressive latent diffusion for 3D molecule generation","created":"2026-07-10","cited_by_count":1,"area":"diffusion"},{"id":"2607.12380","title":"SinAE: A Single-Architecture Flow-Matching Autoencoder for Cross-Domain Atomic Systems","created":"2026-07-14","cited_by_count":1,"area":"diffusion"},{"id":"2607.17910","title":"Chemical filters for ultra-high-throughput materials screening and generation","created":"2026-07-20","cited_by_count":1,"area":null},{"id":"2609.26402","title":"OMatG-flash: An All-Atom Flow Map with Reinforce Adjoint Matching for Scalable Materials Discovery","created":"2026-09-22","cited_by_count":1,"area":"diffusion"},{"id":"2504.17656","title":"polyGen: A Learning Framework for Atomic-level Polymer Structure Generation","created":"2025-04-24","cited_by_count":0,"area":null},{"id":"2512.05080","title":"OMTRA: A Multi-Task Generative Model for Structure-Based Drug Design","created":"2025-12-04","cited_by_count":0,"area":null},{"id":"2601.21527","title":"Sustainable Materials Discovery in the Era of Artificial Intelligence","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2602.02780","title":"Scaling-Aware Adapter for Structure-Grounded LLM Reasoning","created":"2026-02-02","cited_by_count":0,"area":"lr"},{"id":"2602.21533","title":"Reasoning-Driven Design of Single Atom Catalysts via a Multi-Agent Large Language Model Framework","created":"2026-02-25","cited_by_count":0,"area":"agents"},{"id":"2603.06082","title":"Offline Materials Optimization with CliqueFlowmer","created":"2026-03-06","cited_by_count":0,"area":null},{"id":"2605.10115","title":"Generating Symmetric Materials using Latent Flow Matching","created":"2026-05-11","cited_by_count":0,"area":"diffusion"},{"id":"2606.13955","title":"Smoothing Dark Areas in Molecular Latent Diffusion","created":"2026-06-11","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":"2607.19237","title":"DBMol: Design of High-Affinity, Target-Specific Small Molecules through Structure Prediction Models","created":"2026-07-21","cited_by_count":0,"area":null},{"id":"2607.21660","title":"Generative and multimodal AI for materials prediction and design: Progress, challenges, and perspectives","created":"2026-07-22","cited_by_count":0,"area":null},{"id":"2607.24272","title":"Catalyst Diffusion Transformer: Generative Inverse Design of Heterogeneous Catalysts","created":"2026-07-27","cited_by_count":0,"area":null},{"id":"2607.28776","title":"Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation","created":"2026-07-30","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":"2609.15077","title":"Ensemble-Conditioned Molecular Design","created":"2026-09-14","cited_by_count":0,"area":null},{"id":"2609.32502","title":"TreeRef-BFN: Equivariance-Free De Novo Molecule Generation based on 2D Topology and Internal 3D Geometry","created":"2026-09-26","cited_by_count":0,"area":null},{"id":"2609.37158","title":"GLASS: Global Latent Aggregation with Slot-based Set Decoding for Scalable All-Atom Crystal Generation","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.01315","title":"EP-Flow: Disordered Crystal Structure Prediction without Site-Level Annotations","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}