随着大语言模型(LLM)的参数规模增长到数千亿,并开始显示出早期的通用人工智能迹象,它们的应用也已经超越了文本处理。Codex首创将LLM应用于代码处理,取得了令人惊叹的结果,催生了GitHub Copilot等商业产品和Sta…
Evaluation of Language Models for Code 评测任务包括: understanding tasks: clone detection, defect detection sequence-to-sequence tasks generation tasks: code repair, code translation, program synthesis, code summarization 在HumanEval和Codex被引入以后,text-to-code synthesis变成了一个评估LLMs的标准任务。
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A Survey on Language Models for Code.https://www.aminer.cn/pub/65543326939a5f40820ac868/?f=wb本文是一篇关于代码处理中语言模型的系统综述。文章回顾了近期在代码处理方面语言模型的进展,涵盖了50多个模型、30多个评估任务、170多个数据集以及700多个相关研究。作者将代码处理模型分为通用语言模型(以GPT家族为...
NL2Code. To facilitate further research and applications in this field, in this paper, we present a comprehensive survey of 27 existing large language models for NL2Code, and also review benchmarks and metrics. We provide an intuitive comparison of all existing models on the HumanEval bench...
NL2Code. To facilitate further research and applications in this field, in this paper, we present a comprehensive survey of 27 existing large language models for NL2Code, and also review benchmarks and metrics. We provide an intuitive comparison of all existing models on the HumanEval benchmark...
[文献翻译] Retrieval-Augmented Generation for Natural Language Processing: A Survey 自然语言处理中的检索增强生成RAG:综述摘要大语言模型 (LLMs) 在各个领域都取得了巨大的成功,这得益于它们存储知识的巨大参数量。然而,LLMs 仍然存在一些关键问题,例如幻觉问题、知识更… 李常青 文章分享 Large Language Models:...
Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, making them ideal for various settings including on-device, mobile, edge devices, among many others. In this article, we ...
随着人工智能技术的飞速发展,大语言模型(Large Language Models,简称LLMs)已成为近年来最引人瞩目的技术之一。本文旨在通过翻译与解读《A Survey of Large Language Models》这篇综述文章,为读者揭示LLMs的内在机制、发展历程以及所面临的挑战,并探讨它们在现代计算领域中的广泛应用。 首先,我们需要了解LLMs背后的核心...
Large Language Models (LLMs) exhibit strong contextual understanding and remarkable multi-task performance. Therefore, researchers have been seeking to integrate LLMs in the broad sense of Spoken Language Understanding (SLU) field. Different from the traditional method of cascading LLMs to process ...