AsyncFC Framework Enables Parallel Function Calling for LLMs
Researchers have introduced AsyncFC, a framework that allows large language models (LLMs) to execute function calls asynchronously without model changes. Traditional synchronous function calling blocks LLM decoding until each function completes, increasing latency. AsyncFC decouples decoding from execution, enabling overlap and inter-function parallelism when dependencies allow. It requires no fine-tuning or changes to existing synchronous protocols. Benchmarks show significant reductions in end-to-end task completion time while preserving accuracy, revealing that LLMs possess native capability for asynchronous execution.
Key facts
- AsyncFC is a pure execution-layer framework.
- It decouples LLM decoding from function execution.
- No fine-tuning or model changes are required.
- It enables overlap between decoding and execution.
- Inter-function parallelism is supported when dependencies permit.
- Standard function-calling benchmarks show reduced latency.
- Task accuracy is preserved.
- LLMs have native capability for asynchronous execution.
Entities
Institutions
- arXiv