HEF frames emergence as a phase transition in mechanism landscapes with proofs of convergence under structural assumptions, empirically tested via grokking in transformers showing weight-norm peaks and accuracy collapse to ~0.9745.
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Proposes a two-gradient-field model with candidate order parameters alpha_dagger and kappa_c to unify phase transitions across learning theory and non-equilibrium chemistry.
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Emergence via Phase Transitions: Mechanism Landscapes and Universal Convergence Across Complex Systems
HEF frames emergence as a phase transition in mechanism landscapes with proofs of convergence under structural assumptions, empirically tested via grokking in transformers showing weight-norm peaks and accuracy collapse to ~0.9745.
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Phase Transitions in Driven Informational Systems: A Two-Field Perspective on Learning Theory and Non-Equilibrium Chemistry
Proposes a two-gradient-field model with candidate order parameters alpha_dagger and kappa_c to unify phase transitions across learning theory and non-equilibrium chemistry.