Interaction locality is introduced as a task-geometry-aware measurement framework showing that high-level states in recursive models write locally while recursive updates build broader structures on maze, Sudoku, ARC-AGI, and 3D grounding tasks.
Spies, William Edwards, Michael I
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HExA is a training-free agent framework that improves LLM performance on novel physics tasks from 2% to 77% by iteratively designing experiments and composing learned skills.
Human-AI coexistence is best modeled as conditional mutualism under governance, formalized as a multiplex dynamical system whose simulations show stable high-coexistence equilibria only under balanced institutional oversight.
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Interaction Locality in Hierarchical Recursive Reasoning
Interaction locality is introduced as a task-geometry-aware measurement framework showing that high-level states in recursive models write locally while recursive updates build broader structures on maze, Sudoku, ARC-AGI, and 3D grounding tasks.
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Hierarchical Experimentalist Agents
HExA is a training-free agent framework that improves LLM performance on novel physics tasks from 2% to 77% by iteratively designing experiments and composing learned skills.
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A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex Societies
Human-AI coexistence is best modeled as conditional mutualism under governance, formalized as a multiplex dynamical system whose simulations show stable high-coexistence equilibria only under balanced institutional oversight.