Skim: Speculative Execution for Fast and Efficient Web Agents
Skim is a new speculative execution framework designed to enhance the efficiency of web agents. By leveraging predictable website structures, it significantly reduces the cost and latency of web tasks without sacrificing accuracy. The framework has demonstrated a median cost reduction of 1.9 times and a latency decrease of 33.4% across various benchmarks.
- ▪Skim exploits predictable structures of purpose-built websites to improve web agent performance.
- ▪The framework reduces the need for heavyweight components in web-agent tasks.
- ▪Skim has shown to decrease median per-task cost by 1.9x and latency by 33.4% without losing accuracy.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.16565 |
| Publication time | Tue, 19 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-19T04:04:57.272Z |
| Last seen | 2026-05-19T04:04:57.272Z |
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Computer Science > Artificial Intelligence arXiv:2605.16565 (cs) [Submitted on 15 May 2026] Title:Skim: Speculative Execution for Fast and Efficient Web Agents Authors:Mike Wong, Kevin Hsieh, Suman Nath, Ravi Netravali View a PDF of the paper titled Skim: Speculative Execution for Fast and Efficient Web Agents, by Mike Wong and 3 other authors View PDF HTML (experimental) Abstract:Skim is a speculative execution framework for web agents that exploits the predictable structure of purpose-built websites. Today's web-agent expense is not intrinsic to the tasks but a property of how agents are composed: frontier-model inference, browser rendering, and ReAct-style planning are applied to every step of every task regardless of complexity.
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