AsyncTool: Evaluating the Asynchronous Function Calling Capability under Multi-Task Scenarios
📰 ArXiv cs.AI
Learn to evaluate asynchronous function calling in multi-task scenarios with AsyncTool, crucial for efficient large language model-based agents
Action Steps
- Implement AsyncTool to evaluate asynchronous function calling capability
- Run experiments under multi-task scenarios to assess tool response latency impact
- Configure agents to utilize idle time while waiting for tool responses
- Test and compare the efficiency of different agent designs
- Apply findings to optimize agent performance in concurrent task execution
Who Needs to Know This
AI engineers and researchers designing LLM-based agents can benefit from this knowledge to improve overall efficiency in real-world applications
Key Insight
💡 AsyncTool helps evaluate asynchronous function calling capability, crucial for efficient LLM-based agents in real-world applications
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🤖 Evaluate async function calling in multi-task scenarios with AsyncTool! 🚀 Improve efficiency in LLM-based agents 📊
Full Article
Title: AsyncTool: Evaluating the Asynchronous Function Calling Capability under Multi-Task Scenarios
Abstract:
arXiv:2605.27995v1 Announce Type: new Abstract: Large language model (LLM)-based agents have shown strong capabilities in using external tools to solve complex tasks. However, existing evaluations often overlook the temporal dimension of tool use, especially the impact of tool response latency, and are usually limited to single-task settings. In real-world applications, multiple tasks often need to be executed concurrently, and overall efficiency depends on whether an agent can use idle time whi
Abstract:
arXiv:2605.27995v1 Announce Type: new Abstract: Large language model (LLM)-based agents have shown strong capabilities in using external tools to solve complex tasks. However, existing evaluations often overlook the temporal dimension of tool use, especially the impact of tool response latency, and are usually limited to single-task settings. In real-world applications, multiple tasks often need to be executed concurrently, and overall efficiency depends on whether an agent can use idle time whi
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