7 citations · 12 across the 6 of their papers we have counts for
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cs.LG2025★ 1 cited
Graph Diffusion Transformers are In-Context Molecular Designers
Gang Liu, Jie Chen, Yihan Zhu +4
In-context learning allows large models to adapt to new tasks from a few demonstrations, but it has shown limited success in molecular design. Existing databases such as ChEMBL con…
cs.AI2025
Scientific Algorithm Discovery by Augmenting AlphaEvolve with Deep Research
Gang Liu, Yihan Zhu, Jie Chen +1
Large language models hold promise as scientific assistants, yet existing agents either rely solely on algorithm evolution or on deep research in isolation, both of which face crit…
q-bio.BM2025★ 1 cited
MolTextNet: A Two-Million Molecule-Text Dataset for Multimodal Molecular Learning
Yihan Zhu, Gang Liu, Eric Inae +1
Small molecules are essential to drug discovery, and graph-language models hold promise for learning molecular properties and functions from text. However, existing molecule-text d…