9 citations · 38 across the 13 of their papers we have counts for
4 papers · 1 filter
Agentic Deep Graph Reasoning Yields Self-Organizing Knowledge Networks
Markus J. Buehler
We present an agentic, autonomous graph expansion framework that iteratively structures and refines knowledge in situ. Unlike conventional knowledge graph construction methods rely…
In-situ graph reasoning and knowledge expansion using Graph-PReFLexOR
Markus J. Buehler
The pursuit of automated scientific discovery has fueled progress from symbolic logic to modern AI, forging new frontiers in reasoning and pattern recognition. Transformers functio…
AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence
Alireza Ghafarollahi, Markus J. Buehler
The design of alloys is a multi-scale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting exp…
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…