arXiv:2605.20623v1 Announce Type: cross
Abstract: We establish explicit lower bounds for advection-diffusion equations in three settings: a polynomial $dot H^-1$ bound for inviscid shears with $uin L^infty_t W^1,1_y$, a uniform positive lower bound on the mixing scale for diffusive shears, and an exponential $L^2$ bound for rapidly oscillating time-periodic flows. All constants are explicit in the data.
The proofs were generated entirely by a multi-agent math proving system, QED, without expert human intervention, serving as a test of AI’s capability to produce rigorous mathematics.
Training Language Agents to Learn from Experience
arXiv:2605.20477v1 Announce Type: cross Abstract: Language agents can adapt from experience in interactive environments, but current reflection-based methods can only self-correct within a single task