papers

Publications (5)

physics.chem-ph2026

Hypothesis-and-Refinement Learning of Organic Structures from Multimodal Spectroscopic Data

Chengchun Liu, Zhiyuan Yan, Li Yuan +5

Determining molecular structures from spectroscopic data remains fundamentally challenging because the inverse problem is intrinsically underdetermined: individual spectra are spar…

cs.CV2020

Fusing Motion Patterns and Key Visual Information for Semantic Event Recognition in Basketball Videos

Lifang Wu, Zhou Yang, Qi Wang +4

Many semantic events in team sport activities e.g. basketball often involve both group activities and the outcome (score or not). Motion patterns can be an effective means to ident…

cs.CV2022

RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement Learning

Boxuan Zhao, Jun Zhang, Deheng Ye +4

Whole-slide images (WSI) in computational pathology have high resolution with gigapixel size, but are generally with sparse regions of interest, which leads to weak diagnostic rele…

q-bio.BM2026

MoleCode unlocks structural intelligence in large language models

Zhiyuan Yan, Chen Liu, Boxuan Zhao +8

Molecules are graphs, but large language models~(LLMs) are usually asked to reason about them through linear strings. The most popular molecular representation, SMILES, compresses…

physics.chem-ph2026

A Cross-Domain Graph Learning Protocol for Single-Step Molecular Geometry Refinement

Chengchun Liu, Wendi Cai, Boxuan Zhao +1

Accurate molecular geometries are a prerequisite for reliable quantum-chemical predictions, yet density functional theory (DFT) optimization remains a major bottleneck for high-thr…