EMNLP 2024main3 citations
Tools Fail: Detecting Silent Errors in Faulty Tools
Jimin Sun, So Yeon Min, Yingshan Chang, Yonatan Bisk
Abstract
Tools have become a mainstay of LLMs, allowing them to retrieve knowledge not in their weights, to perform tasks on the web, and even to control robots. However, most ontologies and surveys of tool-use have assumed the core challenge for LLMs is choosing the tool. Instead, we introduce a framework for tools more broadly which guides us to explore a model’s ability to detect “silent” tool errors, and reflect on how to plan. This more directly aligns with the increasingly popular use of models as tools. We provide an initial approach to failure recovery with promising results both on a controlled calculator setting and embodied agent planning.
BibTeX
@inproceedings{sun-etal-2024-tools,
title = "Tools Fail: Detecting Silent Errors in Faulty Tools",
author = "Sun, Jimin and
Min, So Yeon and
Chang, Yingshan and
Bisk, Yonatan",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.790/",
doi = "10.18653/v1/2024.emnlp-main.790",
pages = "14272--14289"
}