仓库/Skill 库

展示学术写作与技术传播成果的专业数字作品集。Professional digital portfolio showcasing my academic writing and technical communication work.

接收研究问题 → 检索网页 → 阅读关键页面 → 综合输出带引文与置信度分数的结构化报告。Takes a research question → searches the web → reads key pages → synthesizes a structured report with citations and confidence scores

旨在辅助学术与科研任务的 AI 系统：能自主检索文献、总结论文、整理参考文献，并借助自然语言处理理解研究问题、检索相关信息。AI system designed to assist with academic and scientific research tasks. It can autonomously search for literature, summarize papers, and organize references. Using natural language processing, it understands research questions and retrieves relevant information

完整的 S&P 500 质量评分项目：数据采集与剖析、修正板块/子行业错配、清洗异常值与缺失值、将 5 项指标归一化为综合得分、回答全部 4 个研究问题，并搭建交互式 Power BI 仪表盘Complete S&P 500 Quality Score project: sourced and profiled data, fixed the sector/sub-industry mismatch, cleaned outliers and missing values, normalized 5 metrics into a composite score, answered all 4 research questions, and built an interactive Power BI dashboard.

可复现研究流程，通过改造预训练 LLM tokenizer 降低尼泊尔天城文分词成本：连续/字素感知的 BPE 候选挖掘、基于边际增益的贪心词表选择、保留 ID 的 merge 拼接、基于分解的 embedding 初始化，以及 embedding-only/LoRA/CPT 适配；面向 6GB 笔记本 GPU 调优。Reproducible research pipeline that reduces Nepali Devanagari tokenization tax by retrofitting a pretrained LLM tokenizer: continued/grapheme-aware BPE candidate mining, greedy marginal-gain vocabulary selection, ID-preserving merge splicing, decomposition-based embedding init, and embedding-only/LoRA/CPT adaptation. Tuned for a 6GB laptop GPU.

一款连接 AI 助手与 Sci-Hub 的 MCP 服务器，用于自动化学术研究。专为 RAG 设计，可绕过付费墙、处理验证码、通过 OCR 提取文本，并作为循证推理的主要数据获取器An MCP server that bridges AI assistants with Sci-Hub for automated academic research. Designed for Retrieval-Augmented Generation (RAG), it bypasses paywalls, handles captchas, extracts text via OCR, and serves as the primary data-fetcher for evidence-based reasoning.

应用 AI、可复现研究与可靠工程。Applied AI, reproducible research, and reliable engineering.

面向学术研究与文献综述的 MCP Server。MCP Server for Academic Research & Literature Review

生成式、多模态与 Agentic AI 在教育元宇宙中的系统性综述：应用、架构、挑战与未来方向。Systematic review of Generative, Multimodal, and Agentic AI in the Educational Metaverse: applications, architectures, challenges, and future directions.

基于 Claude Code 的多 Agent 系统，用于自动化文献检索、论文下载、验证与报告生成。Claude Code multi-agent system for automated literature search, paper downloading, verification, and report generation.

基于 CrewAI 的 Agent 系统，用于辅助研究者围绕特定高层级研究问题定义研究项目与假设。This is a CrewAI agent system set up to assist a researcher with defining research projects and hypotheses for a specific high-level research question.

面向人脸域去风格化、结构条件化、评估与质量过滤的紧凑型可复现研究流水线。Compact reproducible research pipeline for face-domain destylization, structural conditioning, evaluation, and quality filtering.

多 Agent AI 研究助手——由多个专门化 Agent 协作，自动检索论文、总结发现、对比方法、生成文献综述并产出可演示的内容Multi-Agent AI Research Assistant — An AI-powered research automation system where multiple specialized agents collaborate to search research papers, summarize findings, compare methodologies, generate literature reviews, and create presentation-ready content.

使用多 Agent RAG 系统与混合索引、LangGraph 编排，自动获取 arXiv 研究论文并生成文献综述。Automate arXiv research paper retrieval and literature review generation using a multi-agent RAG system with hybrid indexing and LangGraph orchestration.

从学术数据库中采集学术元数据，用于组织文献检索与构建研究参考目录。Harvest scholarly metadata from academic databases to organize literature searches and build research bibliographies.

基于 PRISMA 2020 的 LLM 微调技术系统综述（2020–2025）— 84 项研究，涵盖 LoRA/QLoRA/RLHF/DPO，本科毕业论文（PUCE）。PRISMA 2020 systematic review of LLM fine-tuning techniques (2020-2025) - 84 studies, LoRA/QLoRA/RLHF/DPO, undergraduate thesis (PUCE).

基于 LangGraph、LangChain、Groq 和 Tavily 构建的多步骤研究 Agent。分解复杂的研究问题，执行迭代式网络研究，评估证据，并生成结构化的最终报告。Multi-Step Research Agent built with LangGraph, LangChain, Groq, and Tavily. Decomposes complex research questions, performs iterative web research, evaluates evidence, and generates a structured final report.

项目名称：用于自动化文献综述与研究空白发现的自适应 AI 研究智能平台。Project Title: Adaptive AI Research Intelligence Platform for Automated Literature Review and Research Gap Discovery

超强版 PDF 阅读器PDF Reader superpowered

"Domain-Driven Design in Practice: A Large-Scale Empirical Characterisation of the Open-Source Ecosystem" 的复现包——包含数据收集工具、GPT-4o 语义验证流水线，以及针对所有研究问题的 SQL 查询。Replication package for "Domain-Driven Design in Practice: A Large-Scale Empirical Characterisation of the Open-Source Ecosystem" — includes data collection tools, GPT-4o semantic validation pipeline, and SQL queries for all research questions.

面向中英双语生物医学研究的术语循证、主张强度与科学写作审计 skill。Evidence-aligned terminology, claim-strength, and scientific-writing audit skill for Chinese and English biomedical research.

培育持久化数字生命的开放协议：协议、课程、研究问题、治理An open protocol for raising persistent digital beings: protocol, curriculum, research questions, governance

关于 AI Agent 系统与编排的定向研究与文献综述的最终交付成果Final deliverables for directed studies and literature review on AI Agent Systems and Orchestration

推进并系统评估 BV-BRC Copilot，从研究问题和已发表方法生成、执行并复现生物信息学工作流。Advancing and systematically evaluating BV-BRC Copilot for generating, executing, and reproducing bioinformatics workflows from research questions and published methods.

AI agent 辅助学术论文写作。An AI agent supports writing academic papers

用于生成文献综述的全栈系统，基于导入的数据构建，用户可自由选择 LLM。A full stack system use to generate literature review base on dataa imported, users can choose between llms.

Yaroslav Vasylenko —— AI 系统、验证工程、可复现研究与 agentic workflows。Yaroslav Vasylenko — AI systems, verification engineering, reproducible research, and agentic workflows.

学术研究引用管理与论文工具——即时获取洞察，不打断你的专注。立即下载，5 分钟内即可上手运行。Academic Research Citation Manager And Paper — instant insights without breaking your focus. Download now and be running in under 5 minutes.

A/B 测试结果分析，涵盖整体指标评估与精细用户分群。项目结合了变更对结账漏斗各阶段影响的研究、统计假设检验以及不同群体的关键指标评估。Analysis of A/B testing results, covering both an overall assessment of metrics and detailed user segmentation. The project combines research into the impact of changes on the stages of the checkout funnel, testing of statistical hypotheses, and evaluation of key metrics across different groups

基于证据的论文检索与推荐 Agent，面向复杂研究问题。Evidence-grounded paper search and recommendation agent for complex research questions.

基于多 Agent LLM 工作流的智能 AI 学术研究助手，可自动化完成学术论文发现、验证、文献分析、对比矩阵（含表格）、RAG 驱动的研究对话，并产出可直接用于稿件的文献综述An agentic AI academic research assistant that automates academic paper discovery, validation, literature analysis, comparison matrices with table, RAG-powered research chat, and manuscript-ready literature reviews using multi-agent LLM workflows.

基于 LangGraph、LangChain、Groq、ChromaDB 与 Streamlit 构建的多 Agent AI 研究助手，通过联网检索、获取 arXiv 论文、利用 RAG 索引 PDF 并生成有研究依据的回答，实现文献综述自动化Multi-agent AI Research Assistant built with LangGraph, LangChain, Groq, ChromaDB, and Streamlit. Automates literature review by searching the web, retrieving arXiv papers, indexing PDFs with RAG, and generating research-backed answers.

基于 n8n、Google Gemini API、Node.js、React 和 PostgreSQL 构建的多 Agent AI 研究流水线。用户提交研究问题，由规划 Agent 分析并拆解为聚焦的研究子任务，随后由专门 Agent 并行调研主题，覆盖通用研究、技术分析与成本等方面。A multi-agent AI research pipeline built with **n8n, Google Gemini API, Node.js, React, and PostgreSQL**. Users submit a research question that is analyzed by a planning agent and decomposed into focused research tasks. Specialized agents then investigate the topic in parallel, covering areas such as general research, technical analysis, and cost e

面向 AI 饮食评估研究的 3 周入门计划：文献综述、分割、LLM 与 RAG。3-week onboarding plan for AI dietary assessment research: literature review, segmentation, LLMs, and RAG