
ColabWize – Academic Integrity & Collaboration Platform
ColabWize 审计学术引用并验证作者身份,证明学术工作的真实性。
@clawncore · X
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11 projects

ColabWize 审计学术引用并验证作者身份,证明学术工作的真实性。
@clawncore · X


SiteWarming 自动管理和增长您保留的域名价值,无需建站或维护。
@SiteWarming · X
You can try SiteWarming for free! Go ahead and give it a shot🔥

CareerCobra 将职位转化为 ATS 优化的简历和求职信,仅需 30 秒。
@CareerCobraAI · X
We make landing interviews a calculated endeavor, not a lucky chance. Tired of rejections, or simply just re-doing resumes and cover letters over and over again? Give us a shot 🎊

AI驱动的学术论文编辑工具,提供写作辅助、引文管理和查重功能。
Voyagard — AI 学术论文编辑器,有 AI 编辑,一键查重降重,AI推荐文献索引等功能, 帮助你完成从选题调研,文献索引并管理, AI协助撰写等功能,帮助你轻松完成论文撰写

CourseNest 是 AI 职业教练,帮助制作简历、准备面试和找工作。
@DionJerry · X
Promoting We already have over 800 Signups!

上传简历和职位描述,获得针对该职位优化的ATS简历。
u/HungryShake2902 · Reddit
I built the tool I wish I had after years of learning languages, a side project, not another AI tool Hi everyone. I'm 33, originally from Latin America, and I've been living in Europe for almost 10 years. I work full-time in tech sales for an HR company, and programming has never actually been my job, it's just something I've enjoyed for years. I guess I've always been the kind of person who, whenever I run into a problem, starts looking for a solution. What I've noticed is that I don't immed

AI评分工具,包含剽窃检测和学习成果导向的评分表。
@ProfDeskApp · X
Let's connect. Building giving teachers their night back.

管理学术会议:提交和审阅论文、处理日程安排和注册。
@harryjwang · X
I've used many of the major conference systems. Plenty still have docs as an unsearchable static site — or worse, as PDFs that stopped tracking the product three versions ago. Somehow, still true in 2026. We took an AI-first path with instead. Our docs are generated from the codebase itself. A custom Claude Code skill writes each page and retakes the screenshots whenever a feature changes — so the docs don't drift from the product. Every page still gets reviewed by a human before it ships. Now you can talk to them, too. We just shipped "Ask AI" over our docs: This feature also turned out to be a nice teaching case for agentic RAG vs. classic RAG: • Classic RAG: chunk → embed → vector DB → retrieve once, by fixed rules • Agentic RAG: hand the model a search tool and let it drive — write a query, read the results, rewrite, retry At more than 100 pages, still no vector database needed. And every answer cites the exact page it came from. #Age

Arbor Nota — 跨浏览器书签管理器,支持团队文件夹共享。
@TimoPrescott · X
I'm working on my bookmark app, It will allow users to manage all of their bookmarks in a singular Universal location, and it will allow teams the ability to share bookmarks in an intuitive way. I didn't like the existing options, so now I'm here 😎

支持100多种语言的音频和视频转录,使用AI定制简历,查找远程工作机会。
@OauthNature · X
Ai cv tailoring job board