Are LLMs good at structured outputs? A benchmark for evaluating structured output capabilities in LLMs-Reference-Cited by-同舟云学术

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Are LLMs good at structured outputs? A benchmark for evaluating structured output capabilities in LLMs

Published:2024-09 Issue:5 Volume:61 Page:103809
ISSN:0306-4573
Container-title:Information Processing & Management
language:en
Short-container-title:Information Processing & Management

Author:

Liu Yu^ORCID,Li Duantengchuan^ORCID,Wang Kaili,Xiong Zhuoran^ORCID,Shi Fobo^ORCID,Wang Jian,Li Bing,Hang Bo

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference60 articles.

1. LAraBench: Benchmarking arabic AI with large language models;Abdelali,2024

2. Palm 2 technical report;Anil,2023

3. Program synthesis with large language models;Austin,2021

4. Qwen technical report;Bai,2023

5. Baichuan 2: Open large-scale language models;Baichuan,2023

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