Teaching an open model to drive 16,464 real REST APIs: ToolBench built from RapidAPI with no human labels, a depth-first search that lets the model back out of dead ends (DFSDT), an API retriever, and ToolEval to grade it all.
Qin et al. · ICLR 2024 · Reasoning & RL. Read the paper ↗ A free, interactive, animated visual explainer of ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs — every exhibit computed from the real formulas, with verbatim quotes from the source.
Questions #
- What is ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs?
- Teaching an open model to drive 16,464 real REST APIs: ToolBench built from RapidAPI with no human labels, a depth-first search that lets the model back out of dead ends (DFSDT), an API retriever, and ToolEval to grade it all.
- Who published ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs, and where?
- Qin et al. — ICLR 2024 (arXiv:2307.16789).
- Where can I find a visual explainer of ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs?
- Right here — a free, interactive, animated walkthrough of the whole paper, with exhibits computed from the real formulas and verbatim quotes from the source.
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