4 citations · 9 across the 5 of their papers we have counts for
6 papers
Open Polymer Challenge: Post-Competition Report
Gang Liu, Sobin Alosious, Subhamoy Mahajan +9
Machine learning (ML) offers a powerful path toward discovering sustainable polymer materials, but progress has been limited by the lack of large, high-quality, and openly accessib…
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…
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…
Learning Repetition-Invariant Representations for Polymer Informatics
Yihan Zhu, Gang Liu, Eric Inae +2
Polymers are large macromolecules composed of repeating structural units known as monomers and are widely applied in fields such as energy storage, construction, medicine, and aero…
POINT: A Polymer Informatics Training and Testing Database
Jiaxin Xu, Gang Liu, Ruilan Guo +2
The advancement of polymer informatics has been significantly propelled by the integration of machine learning (ML) techniques, enabling the rapid prediction of polymer properties…
Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planning
Gang Liu, Michael Sun, Wojciech Matusik +2
While large language models (LLMs) have integrated images, adapting them to graphs remains challenging, limiting their applications in materials and drug design. This difficulty st…