3 papers indexed
Haipeng Ding, Yuexiang Xie, Zhewei Wei, Yaliang Li, Bolin Ding
Tool utilization enables Large Language Model (LLM) agents to interact with the real world and resolve complex tasks. However, existing agent frameworks predominantly rely on static toolsets composed of granular atomic actions (e.g., basic file I/O or single-turn search), which f…
Wenda Wang, Jinjia Feng, Zhewei Wei
Recent advances in molecular large language models have led to strong performance on molecular understanding and generation tasks, yet these gains often come without reliable structural grounding. In particular, existing approaches conflict with the chemistry principle that struc…
Wenda Wang, Yihan Tong, Yuwei Hu, Zhewei Wei
Using molecular large language models (LLMs) as a unified framework for understanding molecular structures and functions is emerging as a new trend in tasks such as molecular design and drug discovery. However, these models struggle to fully capture the visual representation of m…