5 citations · 9 across the 3 of their papers we have counts for
4 papers
Learning from fracture: Teaching language models to design through physical experience
Bo Ni
How can language models learn to optimize physical designs through experience? We introduce FracLearn, an experience-abstraction-generalization framework evaluated through a delibe…
Agentic End-to-End De Novo Protein Design for Tailored Dynamics Using a Language Diffusion Model
Bo Ni, Markus J. Buehler
Proteins are dynamic molecular machines whose biological functions, spanning enzymatic catalysis, signal transduction, and structural adaptation, are intrinsically linked to their…
MechAgents: Large language model multi-agent collaborations can solve mechanics problems, generate new data, and integrate knowledge
Bo Ni, Markus J. Buehler
Solving mechanics problems using numerical methods requires comprehensive intelligent capability of retrieving relevant knowledge and theory, constructing and executing codes, anal…
ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a protein language diffusion model
Bo Ni, David L. Kaplan, Markus J. Buehler
Through evolution, nature has presented a set of remarkable protein materials, including elastins, silks, keratins and collagens with superior mechanical performances that play cru…