Molecular Optimization

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7 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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In-Context Learning for Latent Space Bayesian Optimization
Jun 8, 2026Tuan A. Vu, Harri Lähdesmäki, Julien MartinelliSynthetic Data Pretraining Molecular Optimization
Aalto University
Closing the Prior-Posterior Loop: Self-Reflective Molecular Design with Analysis-Driven LLM Iteration
Jun 8, 2026Junyi Gong, Zijie Qiu, Ben Zhong TangMolecular Optimization LLM Self-Refinement
Faculty of Chemistry, Shenzhen MSU-BIT University · School of Science and Engineering, Chinese University of Hong Kong (Shenzhen) · Department of Chemistry, Hong Kong University of Science and Technology
Generative Molecular Morphing for Flexible-Size Design via Unbalanced Optimal Transport
Jun 5, 2026Malte Franke, Stefan P. Schmid, Zarko Ivkovic +2Molecular Optimization Molecular Graph Generation
ETH Zürich · NCCR Catalysis
Genotype-Conditioned Molecular Generation via Evidence-Grounded Multi-Objective Latent Perturbation in Diffusion Models
May 31, 2026Brenda Nogueira, Gisela A. Gonzalez-Montiel, Nitesh V. Chawla +1Molecular Optimization Oncology
Department of Computer Science and Engineering University of Notre Dame Notre Dame, IN, 46556 · Department of Chemistry and Biochemistry University of Notre Dame Notre Dame, IN, 46556 · Lucy Family Institute for Data & Society University of Notre Dame Notre Dame, IN, 46556
Fine-Tuning Diffusion Models for Molecular Generation via Reinforcement Learning and Fast Sampling
May 31, 2026Guang Lin, Shikui Tu, Lei XuMolecular Optimization Diffusion Model Fine-Tuning
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, Guangdong, China
Probe Before You Edit: Probing-Guided Molecular Optimization for LLM Agents in Structure-Based Drug Design
May 30, 2026Zaifei Yang, Weiyu Chen, Yaqing Wang +1Molecular Optimization Multi-Agent LLM Systems
1The Hong Kong University of Science and Technology · 2City University of Hong Kong · Beijing Institute of Mathematical Sciences and Applications
Constrained Flow Optimization via Sequential Fine Tuning for Molecular Design
May 28, 2026Sven Gutjahr, Riccardo De Santi, Luca Schaufelberger +2Constrained Generative Modeling Molecular Optimization
Department of Computer Science, ETH Zurich · ETH AI Center · NCCR Catalysis, Switzerland +1
Mixing Vector Model for Copolymer Inference via Mixed Integer Linear Programming
May 28, 2026Jianshen Zhu, Raveena Rai, Taiyo Sohkawa +4Molecular Optimization Materials Property Prediction
Department of Information Science and Technology, Tokyo University of Science, Noda 278-8510, Japan · Discrete Mathematics and Computational Intelligence Laboratory, Department of Mathematics, Quaid-i-Azam University, Islamabad 45320, Pakistan · Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan +3
Closed-Loop Molecular Design with Calibrated Deference
May 27, 2026Newman Cheng, Gordon Broadbent, Jason Dong +11Molecular Optimization AI Agents for Scientific Discovery
Microsoft Discovery & Quantum, Redmond, WA, USA. · Department of Chemical and Environmental Engineering, Yale University, New Haven, CT, USA. · CanAm Bioresearch Inc., Winnipeg, MB, Canada. +1
PhAME: Phenotype-Aware Molecular Editing via Latent Diffusion
May 27, 2026Łukasz Janisiów, Sebastian Musiał, Bartosz Zieliński +2Molecular Optimization Classifier-Free Guidance
Faculty of Mathematics and Computer Science, Jagiellonian University · Doctoral School of Exact and Natural Sciences, Jagiellonian University · Jagiellonian Center for Artificial Intelligence, Jagiellonian University +2
An Evolutionary Approach for Designing Stable and Highly Expressible Low-Immunogenicity Therapeutic mRNA Sequences
May 27, 2026Dhawa Sang Dong, Mausam Gurung, Suraj KandelMolecular Optimization Large Language Model-Guided Optimization
Department of Artificial Intelligence School of Engineering, Kathmandu University Dhulikhel, Nepal · Department of Electronics and Computer Engineering Kathmandu Engineering College, Trivubhan University Kathmandu, Nepal · Hetauda School of Management and Social Science Trivubhan University Hetauda, Nepal
MolLingo: Molecule-Native Representations for LLM-Powered Scientific Agents
May 27, 2026Thao Nguyen, Heng JiMolecular Optimization Multi-Agent LLM Systems
Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign
DGLD: Domain-Gated Latent Diffusion for the Discovery of Novel Energetic Materials
May 26, 2026Yehudit Aperstein, Alexander ApartsinMolecular Optimization Latent Diffusion Models
Department of Intelligent Systems, Afeka Tel-Aviv College of Engineering, Israel. · School of Computer Science, Faculty of Sciences, HIT-Holon Institute of Technology, Israel.
Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models
May 25, 2026Qingyuan Zeng, Pengxiang Cai, Zixin Guan +5Molecular Optimization Molecular Generation
The Hong Kong University of Science and Technology (Guangzhou) · Guangzhou University of Chinese Medicine
Molecular Lead Optimization via Agentic Tool Planning
May 21, 2026Lingxiao Li, Haobo Zhang, Ruohao Fan +2Molecular Optimization Large Language Model-Guided Optimization
University of Michigan Ann Arbor, Michigan, USA · Department of Biochemistry and Molecular Medicine University of California, Davis Davis, California, USA · Department of Pharmacology and Toxicology Michigan State University East Lansing, Michigan, USA
Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization
May 17, 2026Yuan Xue, Daniel Kudenko, Megha KhoslaMolecular Optimization Diffusion Model Fine-Tuning
L3S Research Center, Hanover, Germany · Delft University of Technology, Delft, Netherlands
Controllable Molecular Generative Foundation Models
May 14, 2026Yihan Zhu, Yuhan Liu, Weijiang Li +2Molecular Optimization Molecular Graph Generation
University of Notre Dame
Towards Discovery of Polymers for Insulin Delivery via Physics-Grounded Agentic Workflows
May 12, 2026Martins OtunMolecular Optimization Large Language Model-Guided Optimization
1Algonix AI Ltd., Scotland, United Kingdom
ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery
May 12, 2026Andrew Y. Zhou, Sharvaree Vadgama, Sumanth Varambally +3Molecular Optimization AI Agents for Scientific Discovery
Department of Computer Science and Engineering, UC San Diego, La Jolla, California, United States · Department of Computer Science, Stanford University, Stanford, California · Skaggs School of Pharmacy and Pharmaceutical Sciences, UC San Diego, La Jolla, California
MolDeTox: Evaluating Language Model's Stepwise Fragment Editing for Molecular Detoxification
May 12, 2026Jueon Park, Wonjune Jang, Jiwoo Lee +2Molecular Optimization LLM Evaluation
Korea University · Myongji University · AIGEN Sciences
SLIM: Sparse Latent Steering for Interpretable and Property-Directed LLM-Based Molecular Editing
May 11, 2026Mingxu Zhang, Yuhan Li, Lujundong Li +3Molecular Optimization LLM Interpretability
The Hong Kong University of Science and Technology (Guangzhou) · Nanjing University of Aeronautics and Astronautics · The 63rd Research Institute, National University of Defense Technology, Nanjing
FORGE: Fragment-Oriented Ranking and Generation for Context-Aware Molecular Optimization
May 11, 2026Qingchuan Zhang, He Cao, Hao Li +6Molecular Optimization Large Language Model-Guided Optimization
University of Science and Technology of China · International Digital Economy Academy · Peking University +5
From Single-Step Edit Response to Multi-Step Molecular Optimization
May 11, 2026Haojie Rao, Kun Li, Yida Xiong +5Molecular Optimization Constrained Optimization
School of Computer Science, Wuhan University, Wuhan, China · School of Computer Science, Wuhan University Wuhan, China · Department of Data Science and Artificial Intelligence, Monash University, Victoria, Australia +5
MolWorld: Molecule World Models for Actionable Molecular Optimization
May 9, 2026Yang Qiao, Bo Pan, Hao-Wei Pang +3Molecular Optimization World Models
Emory University · Atlanta, GA, USA · Merck & Co., Inc. +1
SPADE: Faster Drug Discovery by Learning from Sparse Data
May 6, 2026Rahul Nandakumar, Ben Fauber, Deepayan ChakrabartiMolecular Optimization AI-Assisted Scientific Research
McCombs School of Business University of Texas at Austin Austin, TX · NVIDIA
Computational Design and Experimental Validation of Photoactive PARP1 Inhibitors
Apr 27, 2026Simon Axelrod, Miroslav Kašpar, Kristýna Jelínková +8Molecular Optimization Structure-Based Drug Design
Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, 02138 · Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139 · Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo nám. 2, 160 00 Prague 6, Czech Republic
C-MORAL: Controllable Multi-Objective Molecular Optimization with Reinforcement Alignment for LLMs
Apr 24, 2026Rui Gao, Youngseung Jeon, Swastik Roy +2RL for Language Models Molecular Optimization
University of California, Los Angeles · Amazon
Multi-Objective Reinforcement Learning for Generating Covalent Inhibitor Candidates
Apr 21, 2026Renee GilMolecular Optimization Molecular Generation
Independent Researcher
KinetiDiff: Docking-Guided Diffusion for De Novo ACVR1 Inhibitor Design in Fibrodysplasia Ossificans Progressiva
Apr 17, 2026Aaryan PatelMolecular Optimization Diffusion Guidance
Saugus High School, Santa Clarita, CA
LLM-Guided Dynamic Action Spaces for Synthesizable Molecular Optimization
Apr 9, 2026Tao Li, Kaiyuan Hou, Tuan Vinh +4Molecular Optimization Large Language Model-Guided Optimization
Department of Computer Science, Emory University · School of Computer Science, Carnegie Mellon University · MRC Brain Network Dynamics Unit, University of Oxford +3

Jun 8, 2026, cs.LGJ/K move · Enter open · S save

In-Context Learning for Latent Space Bayesian Optimization

Tuan A. Vu, Harri Lähdesmäki, Julien Martinelli

Aalto University

Synthetic Data Pretraining Molecular Optimization Surrogate Modeling Bayesian Optimization Latent Space Optimization Tabular ICL

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Bayesian optimization (BO) is a central tool for sample-efficient design, and latent-space Bayesian optimization (LSBO) extends it to structured objects such as molecules and proteins. In parallel, tabular foundation models such as TabPFN and TabICL now achieve state-of-the-art regression performance and are increasingly used as BO surrogates. Because their Bayesian behavior is induced by large synthetic pretraining collections, the composition of this pretraining distribution is crucial. LSBO creates a distinctive mismatch: the induced map from latent code to objective value differs markedly from the regression tasks used to train current in-context models. We address this mismatch by complementing the pretraining stage of tabular foundation model surrogates with synthetic optimization tasks defined on the latent space of a molecular VAE. The continued-pretraining objective features a regularizer that anchors the model to the original checkpoint, preserving its broad regression prior while avoiding overspecialization to the adaptation tasks. On held-out molecular optimization benchmarks, the resulting model achieves strong performance, supporting the relevance of LSBO-specific adaptation for in-context surrogates.

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