Protein mutation effect generation asks a model to describe the functional consequence of a point mutation in natural language. Existing protein-to-text systems typically encode mutation information into undifferentiated representations, overlooking the organization of mutation-induced evidence across structural and bi...
Liuzhenghao Lv, Yu-Yang Liu, Yu-Yang Gao et al.· 0 citations
The results suggest that integrating persistent execution with session-level provenance can improve the reliability of AI-assisted scientific workflows, and recommend that integrating persistent execution with session-level provenance can improve the reliability of AI-assisted scientific workflows.
Gong-Bo Zhang, Hao Li, Yu Wang et al.· 0 citations
LabEvolver couples a state-grounded inner trial loop for adaptive perception, online planning, and safety validation with an outer evolution loop that distills completed trajectories into reusable skill, strategy, and safety experience, showing generality beyond wet-lab settings.
HME is presented, a framework that combines multiple views of molecules to improve molecular understanding and design and enables bidirectional navigation of the chemical-linguistic space, achieving consistent improvements across molecular comprehension and design tasks over strong baselines.
Liuzhenghao Lv, Hao Li, Yu Wang et al.· Nature Communications· 0 citations
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