agent/papers/items/2026-2602-13665-hyfunc-accelerating-llm-based-function-calls-for-agentic-ai-through-hybrid-model.md

Paper: HyFunc: Accelerating LLM-based Function Calls for Agentic AI through Hybrid-Model Cascade and Dynamic Templating

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type: paper title: "HyFunc: Accelerating LLM-based Function Calls for Agentic AI through Hybrid-Model Cascade and Dynamic Templating" authors: Weibin Liao, Jian-guang Lou, Haoyi Xiong year: 2026 venue: arXiv url: https://arxiv.org/abs/2602.13665 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-02-14 updated_at: 2026-02-14 status: queued relevance: high topics:

• agent-evaluation
• computer-use methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

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related_projects:

collection_score: 13 collection_queries: function-calling

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: function-calling
• inferred topics: agent-evaluation, computer-use
• arXiv categories: cs.AI
• collection score: 13

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2602.13665