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What Are Tools Anyway? A Survey from the Language Model Perspective

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arxiv 2403.15452 v1 pith:WKFIC7LU submitted 2024-03-18 cs.CL cs.AI

classification cs.CLcs.AI
keywords toolsanywaylanguageperformancereviewsurveytaskstool
verification ladder T0 review T1 audit T2 compute T3 formal
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Language models (LMs) are powerful yet mostly for text generation tasks. Tools have substantially enhanced their performance for tasks that require complex skills. However, many works adopt the term "tool" in different ways, raising the question: What is a tool anyway? Subsequently, where and how do tools help LMs? In this survey, we provide a unified definition of tools as external programs used by LMs, and perform a systematic review of LM tooling scenarios and approaches. Grounded on this review, we empirically study the efficiency of various tooling methods by measuring their required compute and performance gains on various benchmarks, and highlight some challenges and potential future research in the field.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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    cs.PL 2025-07 conditional novelty 5.0 of 10

    After matching computational budget, TroVE's toolbox mechanism yields only a marginal, statistically non-significant 1% accuracy gain over a plain sampling baseline on MATH.

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