SparseRead長程閱讀省令牌

Computer Science > Artificial Intelligence arXiv:2608.

22237 (cs) [Submitted on 23 Aug 2026] Title:Read Less, Solve More: Token-Efficient Sparse Reading for AI Agents Authors:Zedong Liu, Jiaan Wu, Xinyang Ma, Le Xu, Kai Wang, Yuanchao Hu, Dingwen Tao, Guangming Tan View a PDF of the paper titled Read Less, Solve More: Token-Efficient Sparse Reading for AI Agents, by Zedong Liu and 7 other authors View PDF Abstract:Long-horizon agents increasingly rely on repeated access to external artifacts, yet current reading interfaces often expose entire objects even when only sparse evidence is needed.

This over-reading increases token and latency costs and can dilute task-relevant evidence, while existing context-reduction methods mainly intervene after broad content has already entered the trajectory.

We present SparseRead, a training-free, model-transparent reading layer that controls content admission before unnecessary evidence reaches the model context.

SparseRead combines a regime-aware Read Gate, extensible Reader Backends, and a stateful protocol for bounded, source-anchored evidence acquisition with explicit refinement, verification, stopping, and fallback.

Across six frontier models, including Claude Opus 5, and five workload scenarios, SparseRead reduces token volume by up to 92.9% and wall time by up to 89.0%, while preserving or improving task quality.Its consistent gains across three agent frameworks further demonstrate broad portability.

Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2608.22237 [cs.AI] (or arXiv:2608.22237v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2608.

22237 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Zedong Liu [view email] [v1] Sun, 23 Aug 2026 06:24:26 UTC (1,340 KB) Full-text links: Access Paper: View a PDF of the paper titled Read Less, Solve More: Token-Efficient Sparse Reading for AI Agents, by Zedong Liu and 7 other authorsView PDFTeX Source view license Current browse context: cs.

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