Bioinspired123D is a generative agentic framework that translates natural language descriptions of biological structure into executable Blender code.
AI & ML interests
PI: Markus J. Buehler, MIT. Our research focus on developing a new paradigm that designs materials from the molecular scale, using MD, ML and other methods.
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Papers
GraphAgents: Knowledge Graph-Guided Agentic AI for Cross-Domain Materials Design
Selective Imperfection as a Generative Framework for Analysis, Creativity and Discovery
models
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lamm-mit/Bioinspired3D
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lamm-mit/Llama3.1-8b-Instruct-CPT-SFT-DPO-09022024-Q4_K_M-GGUF
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lamm-mit/Graph-Preflexor-3b_08012026
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lamm-mit/Graph-Preflexor-1.7b_08012026
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lamm-mit/Graph-Preflexor-8b_12292025
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lamm-mit/LlaDA-8B-EditFlow-graph-v520
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lamm-mit/LlaDA-8B-EditFlow-instruct-v500
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lamm-mit/LlaDA-8B-EditFlow-graph-v510
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lamm-mit/LlaDA-8B-EditFlow-graph-v509
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lamm-mit/LLaDA-8B-Bioinspired-dLLM-Instruct-11-21-2025
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datasets
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lamm-mit/Bioinspired3D
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4.56k
lamm-mit/HyperGraphReasoning
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lamm-mit/graph_reasoning_10K
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lamm-mit/graph_reasoning_1K
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lamm-mit/graph-reasoning-messages-11K
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lamm-mit/scales-12tet-defects
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lamm-mit/graph_reasoning_v3_v4_large
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lamm-mit/PRESTO-protein-force
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lamm-mit/bio-silk-mech-mix-q-a-35K-messages-only
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lamm-mit/tersoff-3atom-toy
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