Crafting the ideal, job-specific resume is a challenging task for many job
applicants, especially for early-career applicants. While it is highly
recommended that applicants tailor their resume to the specific role they are
applying for, manually tailoring resumes to job descriptions and role-specific
requirements is often (1) extremely time-consuming, and (2) prone to human
errors. Furthermore, performing such a tailoring step at scale while applying
to several roles may result in a lack of quality of the edited resumes. To
tackle this problem, in this demo paper, we propose ResumeFlow: a Large
Language Model (LLM) aided tool that enables an end user to simply provide
their detailed resume and the desired job posting, and obtain a personalized
resume specifically tailored to that specific job posting in the matter of a
few seconds. Our proposed pipeline leverages the language understanding and
information extraction capabilities of state-of-the-art LLMs such as OpenAI's
GPT-4 and Google's Gemini, in order to (1) extract details from a job
description, (2) extract role-specific details from the user-provided resume,
and then (3) use these to refine and generate a role-specific resume for the
user. Our easy-to-use tool leverages the user-chosen LLM in a completely
off-the-shelf manner, thus requiring no fine-tuning. We demonstrate the
effectiveness of our tool via a video demo and propose novel task-specific
evaluation metrics to control for alignment and hallucination. Our tool is
available at this https URL

使用大型语言模型 (LLM) 的工具 ResumeFlow，能够根据用户提供的具体工作岗位和详细简历，生成与该工作岗位相匹配的个性化简历。

简历流程：基于 LLM 的个性化简历生成和优化管道

ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume  Generation and Refinement

In this position paper, we elaborate on the possibilities and needs to
integrate Design Thinking into Requirements Engineering. We draw from our
research and project experiences to compare what is understood as Design
Thinking and Requirements Engineering considering their involved artifacts. We
suggest three approaches for tailoring and integrating Design Thinking and
Requirements Engineering with complementary synergies and point at open
challenges for research and practice.

本文阐述了将设计思维与需求工程融合的可能性和需求，并根据其涉及的工件比较了两者的不同。我们提出了三种方法来个性化和整合设计思维和需求工程，以形成互补的协同效应，并指出了研究和实践中面临的挑战。