Key papers

• Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning (2026)
  Chen Tang et al.
  14.56
• Machine-Learned Compact Subspace Generation for Quantum Selected Configuration Interaction within Density Matrix Embedding Framework (2026)
  Ashish Kumar Patra et al.
  5.01
• Neural spectroscopy of AlphaFold2 reveals encoded protein conformational landscapes (2026)
  Kaustav Mehta
  4.39
• Antigen-specific Antibody Multi-modal Foundation Model for Functional Antibody Design (2026)
  Xiaoliang Shi et al.
  4.39
• Multi-modal transformer for signal classification in nanopore blockade experiments (2026)
  Sandro Kuppel et al.
  4.39
• SenCos-GEM: SENet-Calibrated and Law-of-Cosines-Constrained Geometry-Enhanced Molecular Representation for Property Prediction (2026)
  Tianming Han et al.
  4.39
• Graph Learning on Ensembles of Cyclic Peptides: An Investigation of Molecular Ensemble Modeling (2026)
  Aaron Feller et al.
  4.39
• MolSight: A Graph-Aware Vision-Language Model for Unified Chemical Image Understanding (2026)
  Wenda Wang et al.
  3.51
• Diversity-Aware Reinforcement Learning for de novo Drug Design (2024)
  Hampus Gummesson Svensson et al.
  3.42
• From Supervision to Exploration: What Does Protein Language Model Learn During Reinforcement Learning? (2025)
  Hanqun Cao et al.
  3.10
• Pareto-Optimal Offline Reinforcement Learning via Smooth Tchebysheff Scalarization (2026)
  Aadyot Bhatnagar et al.
  1.83
• Agentic AI-assisted coding offers a unique opportunity to instill epistemic grounding during software development (2026)
  Magnus Palmblad et al.
  1.83
• TR2-D2: Tree Search Guided Trajectory-Aware Fine-Tuning for Discrete Diffusion (2025)
  Sophia Tang et al.
  1.44
• Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks (2025)
  Xinyu Wang et al.
  1.22
• Improving Targeted Molecule Generation through Language Model Fine-Tuning Via Reinforcement Learning (2024)
  Salma J. Ahmed et al.
  0.61
• Parallelizing Contextual Bandits (2021)
  Jeffrey Chan et al.
  —
• Distributed Reinforcement Learning for Molecular Design: Antioxidant case (2023)
  Huanyi Qin et al.
  —
• Automating reward function configuration for drug design (2023)
  Marius Urbonas et al.
  —
• Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design (2024)
  Yannick Vogt et al.
  —
• De novo Drug Design using Reinforcement Learning with Multiple GPT Agents (2024)
  Xiuyuan Hu et al.
  —
• Mol-AIR: Molecular Reinforcement Learning with Adaptive Intrinsic Rewards for Goal-directed Molecular Generation (2024)
  Jinyeong Park et al.
  —
• Model-based reinforcement learning for protein backbone design (2024)
  Frederic Renard et al.
  —
• ACEGEN: Reinforcement learning of generative chemical agents for drug discovery (2024)
  Albert Bou et al.
  —
• Reinforcement Learning for Sequence Design Leveraging Protein Language Models (2024)
  Jithendaraa Subramanian et al.
  —
• Token-Mol 1.0: Tokenized drug design with large language model (2024)
  Jike Wang et al.
  —
• Enhancing Molecular Design through Graph-based Topological Reinforcement Learning (2024)
  Xiangyu Zhang
  —