Evaluating Temporal Semantic Caching and Workflow Optimization in Agentic Plan-Execute Pipelines
The article discusses advancements in optimizing industrial asset operations through improved caching and workflow techniques. It highlights the limitations of existing caching methods in handling latency-sensitive queries. The proposed solutions demonstrate significant speed improvements and reduced latency in agentic plan-execute pipelines.
- ▪The study evaluates the performance of asset operations workflows using the AssetOpsBench benchmark.
- ▪Proposed optimizations include a temporal semantic cache and MCP workflow enhancements.
- ▪These optimizations resulted in a 1.67x speedup and a 40% reduction in median end-to-end latency.
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Record
| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.20630 |
| Publication time | Fri, 22 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-22T04:02:00.009Z |
| Last seen | 2026-05-22T04:02:00.009Z |
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| Summary source text | contentText |
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| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
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Computer Science > Artificial Intelligence arXiv:2605.20630 (cs) [Submitted on 20 May 2026] Title:Evaluating Temporal Semantic Caching and Workflow Optimization in Agentic Plan-Execute Pipelines Authors:Alimurtaza Mustafa Merchant, Krish Veera, Sajal Kumar Goyla, Shambhawi Bhure, Dhaval Patel, Kaoutar El Maghraoui View a PDF of the paper titled Evaluating Temporal Semantic Caching and Workflow Optimization in Agentic Plan-Execute Pipelines, by Alimurtaza Mustafa Merchant and 5 other authors View PDF HTML (experimental) Abstract:Industrial asset operations workflows are latency-sensitive because a single user query may require coordination over sensor data, work orders, failure modes, forecasting tools, and domain-specific agents.
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