(3) GPT-3.5 应使用小型训练数据集进行微调。 二、Improving Automated Code Reviews: Learning From Experience https://arxiv.org/pdf/2402.03777.pdf 这篇paper着重挖掘了reviewer的experience,文章指出具有高创作/或审查经验的审阅者来训练模型,并在训练期间过度表示他们的示例。使用这种方法,过采样示例将对模型的行...
Keywords: instruction-tuned LLMs, code comprehension, code generation, defect detection, clone detection, assertion generation, code summarization Paper: 链接 Github: None 论文总结: (1): 本文的研究背景是指导调优大型语言模型在软件工程领域的应用。 (2): 过去的方法主要集中在小型预训练模型上,缺乏对指...
Human programmers tend to use test-driven development for evaluating written code. The program can be considered "correct" if it can pass certain unit tests. The Pass@k Metric To address the limitations of traditional text similarity metrics, the paper introduced the pass@k metric, designed to ...
Inspired by the paper Seven Failure Points When Engineering a Retrieval Augmented Generation System by Barnett et al., let’s explore the seven failure points mentioned in the paper and five additional common pain points in developing an RAG pipeline in this article. More importantly, we will del...
大模型LLM论文整理github.com/km1994/llms_paper LLMs 论文研读社GitHub - km1994/llms_paper: 该仓库主要记录 LLMs 算法工程师相关的顶会论文研读笔记(多模态、PEFT、小样本QA问答、RAG、LMMs可解释性、Agents、CoT)LLMs 论文研读社 RAG 系列篇 RAG Trick篇 RAG 检索Trick篇 RAG 评测篇 RAG应用领域篇 ...
Prompt Flow是一套用于简化基于LLM的人工智能应用的开发工具,缩短端到端的开发周期,支持从构思、原型设计、测试和评估到生产、部署和监控的一体化开发流程。它还提供了一个VS Code扩展,基于UI的交互式流程设计器。 参考资料: https://github.com/microsoft/promptflow ...
products.Microsoft-owned GitHub Copilot, launched in 2021 and widely available from 2022, offers sophisticatedauto-complete features to software developers, including the ability to generate a function based ona natural language description. Similarly, in May 2023 ABB Research published a paper detailing...
ChatPaper: 根据输入关键词,自动在arxiv上下载最新的论文,并对论文进行摘要总结,可以在huggingface上试用 researchgpt:和ChatPDF类似,支持arivx论文下载,加载后对话式获取论文重点 ChatGPT-academic: 又是一个基于gradio实现的paper润色,摘要等功能打包的实现,不少功能可以借鉴 BriefGPT: 日更Arxiv论文,并对论文进...
Code-MVP (MLM + Type Inference + Contrastive Learning): "CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training", 2022-05, NAACL 2022 Technical Track, [paper] Decoder GPT-C (CLM): "IntelliCode Compose: Code Generation Using Transformer", 2020-05, ESEC...
It was developed in 2017 by Google researchers in the paper Attention is All You Need. One of the first experiments to test the potential of transformers was BERT. Launched in 2018 by Google as an open-source LLM, BERT (stands for Bidirectional Encoder Representations from Transformers), ...