AgentQuest: A Modular Benchmark Framework to Measure Progress and Improve LLM Agents

arXiv:2404.06411v1 Announce Type: cross
Abstract: The advances made by Large Language Models (LLMs) have led to the pursuit of LLM agents that can solve intricate, multi-step reasoning tasks. As with any research pursuit, benchmarking and evaluation are key corner stones to efficient and reliable progress. However, existing benchmarks are often narrow and simply compute overall task success. To face these issues, we propose AgentQuest -- a framework where (i) both benchmarks and metrics are modular and easily extensible through well …

agents arxiv benchmark cs.ai cs.cl framework llm modular progress type