Beyond Drug Discovery: The Nanotechnology Molecular Optimization (NMO) Benchmark

arXiv:2606.30170 · cs.LG, cond-mat.mes-hall, cs.AI, cs.CE, physics.chem-ph · Submitted 2026-06-29 · Read on arXiv

cs.LG, cond-mat.mes-hall, cs.AI, cs.CE, physics.chem-ph

Submitted: 2026-06-29

Updated: 2026-09-25

Terminology

• Benchmark — 78× in this paper · explained in 2 episodes
• AUC — 29× in this paper · explained in 2 episodes
• Transformer — 21× in this paper · explained in 2 episodes
• Genetic Algorithm — 14× in this paper
• Group SELFIES — 14× in this paper
• Action Space — 13× in this paper · explained in 1 episode
• Generative Model — 13× in this paper · explained in 2 episodes
• RAG — 13× in this paper · explained in 3 episodes
• Ablation — 12× in this paper · explained in 1 episode
• Molecular Optomechanics — 12× in this paper
• Generative Models — 10× in this paper · explained in 2 episodes
• Core — 8× in this paper · explained in 2 episodes
• Graph Group SELFIES — 7× in this paper
• Structural Constraints — 7× in this paper · explained in 2 episodes
• Adaptive Mechanism — 6× in this paper · explained in 1 episode
• Nanotechnology Molecular Optimization — 6× in this paper
• Ablation study — 5× in this paper · explained in 1 episode
• Accuracy — 5× in this paper · explained in 1 episode
• Alignment — 4× in this paper · explained in 1 episode
• Catastrophic Forgetting — 4× in this paper · explained in 5 episodes
• Failure Modes — 4× in this paper · explained in 3 episodes
• Sample Efficiency — 4× in this paper · explained in 4 episodes
• Transformer Architecture — 4× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 2 episodes
• DFT Calculations — 3× in this paper · explained in 2 episodes
• Inverse Design — 3× in this paper · explained in 2 episodes
• Latent Space — 3× in this paper · explained in 7 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Fidelity — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Mode Collapse — 2× in this paper · explained in 2 episodes
• Multi-objective Optimization — 2× in this paper · explained in 4 episodes
• Negative Log-Likelihood — 2× in this paper
• Physical Constraints — 2× in this paper · explained in 7 episodes
• Quantum Physics — 2× in this paper · explained in 10 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Transferability — 2× in this paper · explained in 4 episodes
• Ab Initio — 1× in this paper · explained in 1 episode
• Accountability — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupled Learning — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Gated Recurrent Unit — 1× in this paper
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Hierarchical Framework — 1× in this paper · explained in 2 episodes
• Hybrid Approach — 1× in this paper · explained in 4 episodes
• International Conference on Learning Representations — 1× in this paper
• International Conference on Machine Learning — 1× in this paper
• Loss Function — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Relevance Indicator — 1× in this paper
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Genetic algorithms are strong baselines for molecule generation

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