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Paper · arXiv 2610.18784

Pack Light, CarryOn: Building Object-Oriented Context for Long-Horizon Agents

Yuchen Lu, Julian McAuley, Lei Zhang

120 upvotesOctober 13, 2026arXiv 预印本
AI 摘要

CarryOn organizes long-horizon agent context around reusable task objects rather than interaction histories, improving efficiency and performance on complex benchmarks.

object-oriented context runtimecontinuation carrierscarrier recordsexecution contextOSWorld 2.0BrowseComp-Plus

Abstract

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 around reusable task objects. Rather than treating compressed histories or reconstructed accounts of progress as the primary basis for continuation, CarryOn builds a context view from continuation carriers, complementary execution context, and a live tail of recent interactions. A core challenge is keeping this reusable basis valid after its surrounding history is retired: how can CarryOn update the basis without reconstructing the full representation at every fold? CarryOn maintains carrier records across folds, revising affected records against bound evidence and applicable environment checks while carrying forward unaffected records and jointly updating execution context. Experiments on OSWorld 2.0 and BrowseComp-Plus show improved gains of 5.8% and 7.0% while reducing total token usage by 51.9% and 22.9%, respectively. Project page: https://ethannju.github.io/carryon

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