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❔ 待判断 科研论文 历史AI 状态:已分析 综合价值 3.9 / 5
来源
arXiv 人工智能预印本(Atom)(arXiv · INTL)
发布时间
2026-10-07 01:26
采集时间
2026-10-07 14:51
语言
en
地域置信度
20%
原始链接
https://arxiv.org/abs/2610.08722v1
内容指纹
6ac6c0090c960827f868836c627ef737681a81cf6d4a63518ca568bddbd839b7

AI 整理

分析于 2026-10-07 14:51(第 1 版,来源:offline)

Many long-horizon agents compact their context on a global rule, usually a token budget, blind to what the agent was doing.We ask whether the agent's recent behaviour predicts when a compaction will h…

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趋势标签: compaction agent predicts context

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Many long-horizon agents compact their context on a global rule, usually a token budget, blind to what the agent was doing. We ask whether the agent's recent behaviour predicts when a compaction will hurt. TRACE's public corpus of 590 harness-triggered AppWorld compaction boundaries replays each boundary from a re-executed prefix state under the pre-compaction context and under the summary, and records the burden of the next actions: calls that error or repeat a call already made. We find that pre-boundary history predicts post-compaction harm only weakly. An internally prespecified contrast by prefix placement is a wide null, and the naive "has-written" label behind it turns out to measure trajectory phase. The best extension-protocol trigger reaches held-out AUROC 0.66 (0.64 on the replicate's own label) against a same-boundary replicate of 0.72; the best frozen, interpretable trigger avoids 21% of harmful (positive-burden) boundaries while keeping 84% of compaction opportunities, and exceeds the random-rule expectation on count but not on burden mass (a post hoc comparison). Whether the best trigger beats a token-budget rule at matched retention cannot be evaluated on the release. We state what corpora should ship to answer it.

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2026-10-07 首次出现
Does an Agent's History Tell You When Compaction Will Hurt? A Modest, Bounded Effect on the TRACE Paired-Replay Corpus

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