新闻
Scores Are Not Decisions: Cost-Aware Stopping for Tool Acquisition in LLM Agents
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers propose CAM-DF, a method to decide how many tools an LLM agent should acquire by balancing relevance against heterogeneous costs like latency and privacy exposure.
- 为何重要
- Matters for engineers building LLM agents that call external APIs, databases, or services where tool acquisition has measurable costs and trade-offs.
- 注意
- Paper is recent preprint; real-world deployment impact beyond the five tested domains remains unclear. Requires existing tool rankings as input.
收听本摘要
- agent
- llm
- retriever
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