Deguang Liu — accepted AI-conference papers

2026

ChemEval: A Multi-level and Fine-grained Chemical Capability Evaluation for Large Language Models

Yuqing Huang, Rongyang Zhang, Xuesong He, Xuyang Zhi, Hao Wang, Nuo Chen +13

ICLR 2026poster

The emergence of Large Language Models (LLMs) in chemistry marks a significant advancement in applying artificial intelligence to chemical sciences. While these models show promising potential, their effective application in chemistry demands sophisticated evaluation protocols that address the field…

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2025

MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights

Jingjing Hu, Dan Guo, Zhan Si, Deguang Liu, Yunfeng Diao, Jing Zhang +2

AAAI 2025technical

Molecular representation learning plays a crucial role in various downstream tasks, such as molecular property prediction and drug design. To accurately represent molecules, Graph Neural Networks (GNNs) and Graph Transformers (GTs) have shown potential in the realm of self-supervised pretraining. Ho…

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