Ye Liu

Thermal neutron density at 10m from the EAS axis linearly correlates with hadron energy on a log scale, offering a new avenue for cosmic ray energy and composition determination.

Progressive semantic refinement no longer requires linear codebook memory growth: reusing a compact set of shared knowledge bases across residual stages achieves multi-depth transmission with a strictly bounded storage footprint.

Because the EVM never validates emitted logs against actual execution state, off-chain bridges and wallets are systematically vulnerable to phantom transactions even when contract code passes traditional logic audits.

Expanding an agent's harness with new tools and skills often degrades its performance on tasks it previously solved, exposing a critical failure mode of "harness-induced forgetting."

Learning RGGs in probabilistic metric spaces reveals that edges can exist with a defined probability, transforming how we understand graph connectivity in complex datasets.