8 citations · 8 across the 1 of their papers we have counts for
7 papers
Towards Unified and Lossless Latent Space for 3D Molecular Latent Diffusion Modeling
Yanchen Luo, Zhiyuan Liu, Yi Zhao +6
3D molecule generation is crucial for drug discovery and material science, requiring models to process complex multi-modalities, including atom types, chemical bonds, and 3D coordi…
NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation
Zhiyuan Liu, Yanchen Luo, Han Huang +7
3D molecule generation is crucial for drug discovery and material design. While prior efforts focus on 3D diffusion models for their benefits in modeling continuous 3D conformers,…
ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining
Zhiyuan Liu, Yaorui Shi, An Zhang +5
Molecule-text modeling, which aims to facilitate molecule-relevant tasks with a textual interface and textual knowledge, is an emerging research direction. Beyond single molecules,…
ProtT3: Protein-to-Text Generation for Text-based Protein Understanding
Zhiyuan Liu, An Zhang, Hao Fei +4
Language Models (LMs) excel in understanding textual descriptions of proteins, as evident in biomedical question-answering tasks. However, their capability falters with raw protein…
Towards 3D Molecule-Text Interpretation in Language Models
Sihang Li, Zhiyuan Liu, Yanchen Luo +5
Language Models (LMs) have greatly influenced diverse domains. However, their inherent limitation in comprehending 3D molecular structures has considerably constrained their potent…
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules
Zhiyuan Liu, Yaorui Shi, An Zhang +4
Masked graph modeling excels in the self-supervised representation learning of molecular graphs. Scrutinizing previous studies, we can reveal a common scheme consisting of three ke…