mlsanityData to 14 Oct 2026

Efficient Evolutionary Search Over Chemical Space with Large Language Models

arXiv 2406.16976 ↗First posted 23 Jun 2024cs.NE cs.AI cs.LGcited by 61

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Abstract (arXiv)

Molecular discovery, when formulated as an optimization problem, presents significant computational challenges because optimization objectives can be non-differentiable. Evolutionary Algorithms (EAs), often used to optimize black-box objectives in molecular discovery, traverse chemical space by performing random mutations and crossovers, leading to a large number of expensive objective evaluations. In this work, we ameliorate this shortcoming by incorporating chemistry-aware Large Language Models (LLMs) into EAs. Namely, we redesign crossover and mutation operations in EAs using LLMs trained on large corpora of chemical information. We perform extensive empirical studies on both commercial and open-source models on multiple tasks involving property optimization, molecular rediscovery, and structure-based drug design, demonstrating that the joint usage of LLMs with EAs yields superior performance over all baseline models across single- and multi-objective settings. We demonstrate that our algorithm improves both the quality of the final solution and convergence speed, thereby reducing the number of required objective evaluations. Our code is available at http://github.com/zoom-wang112358/MOLLEO

Key facts. Cited by 61 papers in the map (data through 14 Oct 2026). Builds on 48 of its 89 references that are in the map. First posted on arXiv 23 Jun 2024.

Builds on

48 of 89 references.

References · 48

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  3. 2023Large Language Models as Optimizerscited by 864
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  11. 2020ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Predictioncited by 337
  12. 2020GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generationcited by 305
36 more
  1. 2017Molecular De Novo Design through Deep Reinforcement Learningcited by 267
  2. 2021Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Developmentcited by 264
  3. 2023SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Modelscited by 256
  4. 2018Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Predictioncited by 229
  5. 2022Structure-based Drug Design with Equivariant Diffusion Modelscited by 217
  6. 2020MoFlow: An Invertible Flow Model for Generating Molecular Graphscited by 185
  7. 2023What can Large Language Models do in chemistry? A comprehensive benchmark on eight taskscited by 185
  8. 2022Translation between Molecules and Natural Languagecited by 177
  9. 2022Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editingcited by 166
  10. 2022Sample Efficiency Matters: A Benchmark for Practical Molecular Optimizationcited by 155
  11. 2022Evolution through Large Modelscited by 134
  12. 2023Large Language Models as Evolutionary Optimizerscited by 124
  13. 2019GraphNVP: An Invertible Flow Model for Generating Molecular Graphscited by 116
  14. 2021Geometric Deep Learning on Molecular Representationscited by 113
  15. 2023The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4cited by 112
  16. 2023BioT5: Enriching Cross-modal Integration in Biology with Chemical Knowledge and Natural Language Associationscited by 100
  17. 2023Unifying Molecular and Textual Representations via Multi-task Language Modellingcited by 93
  18. 2019MolecularRNN: Generating realistic molecular graphs with optimized propertiescited by 82
  19. 2024ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterizationcited by 61
  20. 2020Accelerating high-throughput virtual screening through molecular pool-based active learningcited by 59
  21. 2023Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB filescited by 59
  22. 2023DrugAssist: A Large Language Model for Molecule Optimizationcited by 59
  23. 2022Pareto Set Learning for Neural Multi-objective Combinatorial Optimizationcited by 56
  24. 2021Differentiable Scaffolding Tree for Molecular Optimizationcited by 53
  25. 2023Sample-efficient Multi-objective Molecular Optimization with GFlowNetscited by 50
  26. 2024A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?cited by 48
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  36. 2024Navigating Chemical Space with Latent Flowscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 27; 2026: 29.

61 papers.

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  1. 2025AlphaEvolve: A coding agent for scientific and algorithmic discoverycited by 867
  2. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 126
  3. 2025Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Expertscited by 96
  4. 2025Feedback Descent: Open-Ended Text Optimization via Pairwise Comparisoncited by 44
  5. 2024The Superposition of Diffusion Models Using the Ito Density Estimatorcited by 36
  6. 2024LICO: Large Language Models for In-Context Molecular Optimizationcited by 26
  7. 2025A Survey on LLM Test-Time Compute via Search: Tasks, LLM Profiling, Search Algorithms, and Relevant Frameworkscited by 21
  8. 2025DrugPilot: LLM-based Parameterized Reasoning Agent for Drug Discoverycited by 19
  9. 2024SmileyLlama: Modifying Large Language Models for Directed Chemical Space Explorationcited by 14
  10. 2025LLM-Augmented Chemical Synthesis and Design Decision Programscited by 13
  11. 2025LLEMA: Evolutionary Search with LLMs for Multi-Objective Materials Discoverycited by 13
  12. 2026AIRA_2: Overcoming Bottlenecks in AI Research Agentscited by 12
38 more
  1. 2026LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMscited by 12
  2. 2025A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solvingcited by 11
  3. 2025POLO: Preference-Guided Multi-Turn Reinforcement Learning for Lead Optimizationcited by 11
  4. 2025Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physicscited by 11
  5. 2024Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impactcited by 9
  6. 2025ExLLM: Experience-Enhanced LLM Optimization for Molecular Design and Beyondcited by 8
  7. 2025AutoG: Towards automatic graph construction from tabular datacited by 7
  8. 2025MatLLMSearch: Crystal Structure Discovery with Evolution-Guided Large Language Modelscited by 7
  9. 2025Learning Flexible Forward Trajectories for Masked Molecular Diffusioncited by 7
  10. 2025Towards autonomous quantum physics research using LLM agents with access to intelligent toolscited by 7
  11. 2026LLM-ACES: Closed-Loop Discovery of Dynamical Systems with LLM-Guided Adaptive Searchcited by 7
  12. 2025AutoChemSchematic AI: Agentic Physics-Aware Automation for Chemical Manufacturing Scale-Upcited by 6
  13. 2025The Rise of Generative AI for Metal-Organic Framework Design and Synthesiscited by 6
  14. 2026Reference-guided Policy Optimization for Molecular Optimization via LLM Reasoningcited by 6
  15. 2025Neural Genetic Search in Discrete Spacescited by 5
  16. 2026TritonDFT: Automating DFT with a Multi-Agent Frameworkcited by 5
  17. 2024Generative Design of Functional Metal Complexes Utilizing the Internal Knowledge of Large Language Modelscited by 4
  18. 2026MolEvolve: LLM-Guided Evolutionary Search for Interpretable Molecular Optimizationcited by 4
  19. 2026SMDD-Bench: Can LLMs Solve Real-World Small Molecule Drug Design Tasks?cited by 4
  20. 2026Self-Improving Language Models with Bidirectional Evolutionary Searchcited by 4
  21. 2025MiST: Understanding the Role of Mid-Stage Scientific Training in Developing Chemical Reasoning Modelscited by 3
  22. 2026ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discoverycited by 3
  23. 2026Towards Diverse Scientific Hypothesis Search with Large Language Modelscited by 3
  24. 2025Diffusion-based Evolutionary Optimization for 3D Multi-Objective Molecular Generationcited by 2
  25. 2025GP-MoLFormer-Sim: Test Time Molecular Optimization through Contextual Similarity Guidancecited by 2
  26. 2025Hypothesis Hunting with Evolving Networks of Autonomous Scientific Agentscited by 2
  27. 2025Large Scale Multi-Task Bayesian Optimization with Large Language Modelscited by 1
  28. 2025MCCE: A Framework for Multi-LLM Collaborative Search in Discrete Spaces with Similarity-Filtered Preference Learningcited by 1
  29. 2025Coder as Editor: Code-driven Interpretable Molecular Optimizationcited by 1
  30. 2026SEISMO: Explanation-Aware, Trajectory-Conditioned LLM Agents for Sample-Efficient Molecular Optimisationcited by 1
  31. 2026DrugSAGE:Self-evolving Agent Experience for Efficient State-of-the-Art Drug Discoverycited by 1
  32. 2026Agents on a Tree: Pathwise Coordination for Multi-Objective Molecular Optimizationcited by 1
  33. 2026Sample Efficient Generative Optimization for Molecular Designcited by 1
  34. 2026ATLAS: A Foundation Neural Sampler for Amorphous Materialscited by 1
  35. 2026Recipes for Steering and Scaling LLMs via Samplingcited by 1
  36. 2025Informing Acquisition Functions via Foundation Models for Molecular Discoverycited by 0
  37. 2026INDIBATOR: Diverse and Fact-Grounded Individuality for Multi-Agent Debate in Molecular Discoverycited by 0
  38. 2026MolLIBRA: Genetic Molecular Optimization with Multi-Fingerprint Surrogates and Text-Molecule Aligned Criticcited by 0

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