Molecular Generation

Follow this topic Ask about this topic

Momentum

16 papers in the last four weeks, up 220% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 172

All topics

Evolutionary Curriculum Learning Improves Biological Sequence Modeling
Aug 1, 2026Richard Zhu, Kento NishiVariational Autoencoders Curriculum Learning
Department of Computer Science, Harvard University, Cambridge, MA, USA · Department of Statistics, Harvard University, Cambridge, MA, USA.
A Synthetically-accessible Universe of Chemically Recyclable Polymers
Jul 31, 2026Anagha Savit, Wei Xiong, Harikrishna Sahu +3Synthetic Data Generation Materials Science
School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA · 2Matmerize Inc., Atlanta, GA 30332, USA · School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA
MolGVR: A Chemistry-Grounded Framework for Text-to-Molecule Generation
Jul 31, 2026Qian Tan, Xuanyu Zhu, Lei Jiang +3Molecular Generation Text Generation
University of Science and Technology of China · Shanghai Jiao Tong University · Shanghai Artificial Intelligence Laboratory
Oracle-Budgeted Molecular Optimization with Short-Term Graph Memory
Jul 30, 2026Jiannan Yang, Veronika Thost, Xiang Ling +1Molecular Optimization Surrogate-Assisted Optimization
Computer Science Stony Brook University Stony Brook, New York, USA · Molecular AI Novo Nordisk Lexington, Massachusetts, USA · Biomedical Engineering Stony Brook University Stony Brook, New York, USA +1
SE(3)-MeanFlow: Few-Step Protein Backbone Generation on Lie Groups
Jul 29, 2026Yikun Bai, Binghang Lu, Yikai Liu +7Flow Matching Lie Group Methods
Department of Mathematics, Purdue University · School of Electrical and Computer Engineering, Purdue University · Department of Biochemistry, Purdue University +5
MS-GPT: Rethinking MS/MS De Novo Structure Elucidation as Spectrum-Induced Posterior Querying of a Molecule-Language Model
Jul 26, 2026Xin Zhao, Yumin Liu, Zhuo Li +5Language Modeling Molecular Generation
Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling
Jul 26, 2026Hengyuan Cao, Shizhuo Cheng, Mingxuan Liu +5Molecular Generation Protein Design
Zhejiang University, Hangzhou, China · Fudan University, Shanghai, China · Shanghai Institute for Advanced Study Zhejiang University, Shanghai, China +1
TriGlue: a Biology-Inspired Generative Model for Generating Molecular Glue-Induced Ternary Complex
Jul 24, 2026Yuliang Yan, Shuo Yan, Haochun Tang +2Molecular Generation Drug Discovery
The Hong Kong University of Science and Technology (Guangzhou) · Jilin University · University of Sydney
OLEDLM: A Unified Language Model for OLED Molecular Design
Jul 22, 2026Fukang Wen, Yuchong Tang, Jingyuan Li +9Molecular Optimization Materials Science
1Tsinghua University · 5MathonAI Team · 2Beijing Institute of Mathematical Sciences and Applications +2
Hypothesis-and-Refinement Learning of Organic Structures from Multimodal Spectroscopic Data
Jul 22, 2026Chengchun Liu, Zhiyuan Yan, Li Yuan +5Molecular Generation
School of AI for Science, Peking University Shenzhen Graduate School, Shenzhen 518055, China · State Key Laboratory of Advanced Waterproof Materials, School of Materials Science and Engineering, Peking University, Beijing 100871, China · School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen 518055, China +6
Boltzmann-Expected Molecular Design with Decoupled Annealing Flows
Jul 21, 2026Selma Moqvist, Richard Beckmann, Ross Irwin +2Molecular Optimization Molecular Graph Generation
Department of Computer Science and Engineering Chalmers University of Technology & University of Gothenburg SE-41296 Gothenburg, Sweden · Molecular AI Discovery Sciences, R&D AstraZeneca SE-43183 Mölndal, Sweden
DBMol: Design of High-Affinity, Target-Specific Small Molecules through Structure Prediction Models
Jul 21, 2026Yiming Qin, Kai Yi, Miruna Cretu +3Protein-Ligand Binding Affinity Prediction Molecular Optimization
EPFL, Switzerland · MRC-LMB, UK · University of Cambridge, UK
Parallel Noising in Neural Markov Logic Networks
Jul 21, 2026Peter Jung, Giuseppe Marra, Ondrej KuzelkaMarkov Chain Monte Carlo Graph Generation
Czech Technical University, Prague, Czech Republic · Department of Computer Science, KU Leuven, Leuven, Belgium
Adopting Reinforcement Learning with Verifiable Rewards for Molecular Generation
Jul 21, 2026Mingxuan Ouyang, Hao Lan, Wanyu LinMolecular Optimization Reinforcement Learning with Verifiable Rewards
Decafs: Disentangled Conditional adversarial Flows
Jul 21, 2026Anirudh jain, Sakshi Varshney, Samuel Kaski +1Disentangled Representation Learning Normalizing Flows
Orion Pharma · Aalto University, Finland · Aalto University +3
MotifRole-Diff: Risk-Optimal Role-Aware Corruption for Masked Molecular Graph Diffusion
Jul 20, 2026Tasfia Nuzhat Ornee, Elias Hossain, Ivan Garibay +1Masked Diffusion Models Molecular Graph Generation
University of Central Florida
Do Language Models Dream of Binding Molecules? Benchmarking LLMs under Spatial Constraints
Jul 20, 2026Thomas MacDougall, Maksim Kuznetsov, Roman Schutski +5Constrained Generative Modeling LLM Evaluation
Insilico Medicine Canada Inc. · Insilico Medicine Hong Kong Ltd. · Insilico Medicine AI Limited
HEDGEHOG: Hierarchical Evaluation of Drug Generators Through Rigorous Filtration
Jul 14, 2026Daria A. Ryabchenko, Pavel Gurevich, Shamil Kadyrov +5Molecular Generation Generative AI Evaluation
Ligand Pro, Moscow, Russia · Skolkovo Institute of Science and Technology, Artificial Intelligence Center, Moscow, Russia · 1Ligand Pro, Moscow, Russia +1
Sample Efficient Generative Optimization for Molecular Design
Jul 14, 2026Sarina Kopf, Cristina Nevado, Philippe SchwallerMolecular Optimization Surrogate-Assisted Optimization
LIAC, ISIC, EPFL, Lausanne, Switzerland · Department of Chemistry, University of Zurich, Zurich, Switzerland · Centre of Competence in Research (NCCR) Catalysis, Zurich, Switzerland
SinAE: A Single-Architecture Flow-Matching Autoencoder for Cross-Domain Atomic Systems
Jul 14, 2026Yuxuan Ren, Fan Yang, Jianhua Yao +1Autoencoders 3D Molecular Generation
Department of Computer Science National University of Singapore · Tencent AI for Life Science Lab
Generating Developable 3D Molecules via Pocket-Conditioned Diffusion and Property-Aware Optimization
Jul 14, 2026Ruoxi Gao, Jiangweizhi Peng, Ziqi Chen +10Molecular Optimization Structure-Based Drug Design
Computer Science and Engineering, The Ohio State University, Columbus, OH 43210. · Industrial and System Engineering, University of Minnesota, Minneapolis, MN 55455. · Google Cloud, Google LLC, Mountain View, CA 94043. +6
Gene Expression-Informed Jointly Controlled Generative Modeling for Precision Molecular Design
Jul 13, 2026Hang Yuan, Chen Li, Wenjun Ma +2Molecular Optimization Molecular Generation
School of Artificial Intelligence South China Normal University Foshan, Guangdong, China · D3 Center The University of Osaka Suita, Osaka, Japan · School of Computer Science South China Normal University Guangzhou, Guangdong, China
Vilya-1: An all-atom foundation model for macrocycle structure prediction and design
Jul 10, 2026Vilya Research, :, Pascal Sturmfels +8Molecular Generation Molecular Property Prediction
Vilya Research
Autoregressive latent diffusion for 3D molecule generation
Jul 10, 2026Federico Ottomano, Gaopeng Ren, Yingzhen Li +2Latent Diffusion Models Molecular Graph Generation
Department of Chemistry Imperial College London · Department of Computing Imperial College London
DrugGen 2: A disease-aware language model for enhancing drug discovery
Jul 9, 2026Ali Motahharynia, Mohammadreza Ghaffarzadeh-Esfahani, Mahsa Sheikholeslami +4Molecular Generation Conditional Generative Modeling
Regenerative Medicine Research Center, Isfahan University of Medical Sciences, Isfahan, Iran · Isfahan Neuroscience Research Center, Isfahan University of Medical Sciences, Isfahan, Iran · Department of Medicinal Chemistry, School of Pharmacy, Isfahan University of Medical Sciences, Isfahan, Iran +3
MARLIN: De Novo Molecular Structure Elucidation from Tandem Mass Spectra without a Ground-Truth Formula
Jul 6, 2026Xujun Che, Xiuxia Du, Depeng XuMolecular Generation Mass Spectrometry
Department of Software and Information Systems, University of North Carolina at Charlotte, Charlotte, NC 28223 · Center for Environmental Monitoring and Informatics Technologies for Public Health, University of North Carolina at Charlotte, Charlotte, NC 28223 · Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, NC 28223
AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms
Jul 3, 2026Emmanuel Bengio, Sanjeev Raja, Yui Tik Pang +5Free Energy Calculation Generative Modeling
Valence Labs · Recursion · UC Berkeley
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
Jul 1, 2026Miruna Cretu, John Bradshaw, Patricia Suriana +6Latent Diffusion Models 3D Molecular Generation
University of Cambridge, Cambridge, UK · Prescient Design (AI for Drug Discovery), Genentech, South San Francisco, USA · Work done during an internship at Prescient Design
MolSafeEval: A Benchmark for Uncovering Safety Risks in AI-Generated Molecules
Jul 1, 2026Tong Xu, Xinzhe Cao, Zhihui Zhu +2Molecular Generation
Zhejiang University · ZJU-Hangzhou Global Scientific and Technological Innovation Center · University of Oxford
Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark
Jun 29, 2026Matthias Blaschke, Daniel Kienzle, Zsuzsanna Koczor-Benda +3Molecular Optimization Benchmark Design
University of Augsburg · CAAPS† · Germany +2

Aug 1, 2026, cs.AIJ/K move · Enter open · S save

Evolutionary Curriculum Learning Improves Biological Sequence Modeling

Richard Zhu, Kento Nishi

Department of Computer Science, Harvard University, Cambridge, MA, USA · Department of Statistics, Harvard University, Cambridge, MA, USA.

Variational Autoencoders Curriculum Learning Molecular Generation Sequence Modeling

Open paper AskPDF arXiv

Variational autoencoders (VAEs) trained on multiple sequence alignments (MSAs) have emerged as powerful generative models for biological sequences, with applications ranging from disease variant prediction to functional RNA design. However, standard biological VAE training treats all sequences as exchangeable, ignoring the rich evolutionary structure that organizes homologous sequences from evolutionarily close to highly divergent. We propose Evolutionary Curriculum Learning (ECL), a training strategy that exploits this structure by progressively exposing the model to sequences of increasing evolutionary distance from sampled anchors, following a power-law expansion schedule. Applied to two architecturally distinct VAE models and two biological domains--protein variant effect prediction with EVE and RNA family sequence generation with RfamGen--ECL improves downstream task performance across five random seeds per configuration. Mean ClinVar classification AUROC rises from 0.981 to 0.989 for p53; for PTEN, ECL attains 1.000 in every seed whereas the baseline is unstable (mean 0.905, falling as low as 0.54). For RNA, ECL raises mean covariance-model bit scores on all three families tested and exceeds its seed-matched baseline in 12 of 15 training runs, though with only three families the effect cannot be established as significant at the family level. Ablation experiments show that progressively expanding the sampled sequences by evolutionary distance outperforms fixed-size neighborhood sampling in addition to uniform random sampling. Evolutionary distance is therefore a useful inductive bias for ordering the training curriculum in biological sequence modeling.

Momentum

Related topics

Latest papers 172