Paper recorded by Signals 4 on 2026-10-13 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-13 on arXiv · recorded by Signals 4 on 2026-10-14
Category: cs.AI · 人工智能 · first seen 2026-10-14
Long-horizon agents accumulate progress in persistent task state, yet repeatedly process interaction histories describing how that progress was achieved. This raises a natural question: can long-horizon context instead be organized around reusable progress rather than the history that produced it? In this paper, we introduce CarryOn, an object-oriented context runtime that organizes continuation a