Tool Usage Evaluation Benchmark

Tool usage evaluation benchmarks are being developed to assess the ability of large language models (LLMs) and other algorithms to effectively utilize external tools to solve complex tasks. Current research focuses on creating benchmarks that evaluate not only the successful application of tools but also the crucial decision-making process of *whether* and *which* tools to use, addressing issues like hallucination and inefficient tool selection. These benchmarks are vital for advancing the development of more robust and reliable AI systems, providing a standardized framework for comparing different models and guiding the design of more effective tool-augmented AI architectures.