{"url":"/dataset/stabletoolbench","name":"StableToolBench","full_name":null,"description_markdown":"StableToolBench is a new benchmark for tool learning that aims to provide a well-balanced combination of stability and reality, building upon its predecessor, ToolBench. It was developed to address the instability issues of previous tool learning benchmarks, which either relied on hand-crafted online tools with limited scale or large-scale real online APIs that suffered from instability due to API status changes¹².\r\n\r\nHere are some key features of StableToolBench:\r\n- **Virtual API System**: This includes a caching system to ensure consistent API call responses and API simulators, powered by Large Language Models (LLMs), for unavailable APIs. It maintains the diverse API environment from ToolBench¹.\r\n- **New Set of Solvable Queries**: It uses state-of-the-art LLMs to determine task solvability beforehand, reducing randomness and instability in query solvability¹.\r\n- **Stable Evaluation System**: Implements a two-phase evaluation process using GPT-4 as an automatic evaluator, with metrics like Solvable Pass Rate (SoPR) and Solvable Win Rate (SoWR) to assess the capability of LLMs to utilize tools².\r\n\r\n(1) THUNLP-MT/StableToolBench - GitHub. https://github.com/THUNLP-MT/StableToolBench.\r\n(2) StableToolBench: Towards Stable Large-Scale Benchmarking on Tool .... https://arxiv.org/abs/2403.07714.\r\n(3) StableToolBench: Towards Stable Large-Scale Benchmarking on Tool .... https://paperreading.club/page?id=214642.\r\n(4) Papers with Code - StableToolBench: Towards Stable Large-Scale .... https://paperswithcode.com/paper/stabletoolbench-towards-stable-large-scale.\r\n(5) undefined. https://doi.org/10.48550/arXiv.2403.07714.","description_withheld":null,"homepage":"https://github.com/THUNLP-MT/StableToolBench","introduced_date":"2024-03-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/stabletoolbench-towards-stable-large-scale","title":"StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models","first_author":"Zhicheng Guo","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["StableToolBench"],"data_loaders":[],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}