papers

Publications (5)

cs.LG2024

BatGPT-Chem: A Foundation Large Model For Retrosynthesis Prediction

Yifei Yang, Runhan Shi, Zuchao Li +4

Retrosynthesis analysis is pivotal yet challenging in drug discovery and organic chemistry. Despite the proliferation of computational tools over the past decade, AI-based systems…

cs.LG2026

Learning Molecular Chirality via Chiral Determinant Kernels

Runhan Shi, Zhicheng Zhang, Letian Chen +2

Chirality is a fundamental molecular property that governs stereospecific behavior in chemistry and biology. Capturing chirality in machine learning models remains challenging due…

cs.LG2026

Reaction Prediction via Interaction Modeling of Symmetric Difference Shingle Sets

Runhan Shi, Letian Chen, Gufeng Yu +1

Chemical reaction prediction remains a fundamental challenge in organic chemistry, where existing machine learning models face two critical limitations: sensitivity to input permut…

cs.AI2025

RTMol: Rethinking Molecule-text Alignment in a Round-trip View

Letian Chen, Runhan Shi, Gufeng Yu +1

Aligning molecular sequence representations (e.g., SMILES notations) with textual descriptions is critical for applications spanning drug discovery, materials design, and automated…

cs.AI2026

MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation

Runhan Shi, Quan Zhou, Yuqian Xu +14

The paper presents MedRealMM, a large-scale benchmark of real Chinese online medical consultations that includes both text and patient-uploaded images, and evaluates how well large…

#multimodal learning#medical consultation#large language models#clinical evaluation