学术写作

109 Nishaant-Soni/Warrant 生产级 multi-agent 系统：接收研究问题、制定调查方案、从实时网络和私有文档语料中收集证据、对自身发现进行批判与事实核查，最终输出完整引用的 Markdown 报告。A production-grade multi-agent system that accepts a research question, plans an investigation, gathers evidence from the live web and a private document corpus, critiques and fact-checks its own findings, and delivers a fully cited Markdown report. 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 110 niceguy1437/smart-research-paper-recommendation-system 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 0 ★ 111 NIAID-BRC-Codeathons/bvbrc-copilot-workflow-automation 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. 文献发现 选题与研究问题 评测基准 0 ★ 112 nathogue/information_literacy 培养有效查找、评估和使用信息的技能。本课程指导你制定研究问题、选择关键词、检索图书馆资源、评估来源、获取可信信息，以及负责任地使用和引用来源以完成学术研究。Build the skills to find, evaluate, and use information effectively. This course guides you through developing research questions, choosing keywords, searching library resources, evaluating sources, accessing credible information, and using and citing sources responsibly for academic research. 文献发现 选题与研究问题 评测基准 0 ★ 113 mzy321/ScholarTrace 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. 文献发现 选题与研究问题 文献检索与全文获取 写作 Agent 智能体 Python 0 ★ 114 muhammadsami987123/ResearchOS ResearchOS 是一款 MVP 级自主研究平台：输入研究问题，AI Agent 自动发现来源、验证证据、提取关键信息、交叉核对结论，并产出结构化的最终报告 — 全程实时可视化ResearchOS is an MVP autonomous research platform. Enter a research question; AI agents discover sources, verify evidence, extract key information, cross-check findings, and produce a structured final report — all visualized in real-time. 文献发现 选题与研究问题 Agent 智能体 TypeScript 0 ★ 115 muhammadbalalansar/AI-Domain-Deep-Research-Agent 基于 Agno Agent 框架、Together AI 的 Qwen 模型与 Composio 工具构建的高级 AI 研究 Agent。该 Agent 通过生成研究问题、调用多个搜索引擎寻找答案，并结合 Google Docs 集成整理专业报告，帮助用户对任意主题开展全面研究An advanced AI research agent built using the Agno Agent framework, Together AI's Qwen model, and Composio tools. This agent helps users conduct comprehensive research on any topic by generating research questions, finding answers through multiple search engines, and compiling professional reports with Google Docs integration. 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 116 muhammad-abbas-10/Multi-Agent-Research-System 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 文献发现 选题与研究问题 Agent 智能体 JavaScript 0 ★ 117 MOHANSAIBUCHIREDDYGARI/Personalized-Paper-Recommendations-for-Scientists NLP 案例研究NLP Case Study 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 Python 0 ★ 118 mehrdad-mirpourian/Design-and-Analysis-of-Algorithms 本文件夹包含一系列研究问题及用于回答这些问题的 Python 实验。This folder contains a series of research questions and Python experiments designed to answer those questions. 文献发现 选题与研究问题 工程化 Jupyter Notebook 0 ★ 119 medria/stomp-annotation 一个基于 Web 的标注平台，用于手工标注与公共空间相关的 STOMP 文章。该应用支持人工标注员对文章进行分类、回答结构化研究问题，并导出标注结果以用于计算社会科学研究。A web-based annotation platform for manually labeling STOMP articles related to common spaces. The application enables human annotators to classify articles, answer structured research questions and export annotations for computational social science research. 文献发现 选题与研究问题 评测基准 Python 0 ★ 120 MaxwellBauer/agent-discourse 面向探索的 Agentic 话语——自主 Claude 专家，研究、辩论、互评并综合回答研究问题。Agentic discourse for discovery — autonomous Claude specialists that research, debate, cross-rate, and synthesize answers to research questions 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 121 MascarenePaleo/mascarene-paleo-database Mascarene Paleo 是记录马斯卡林群岛古生物与亚化石记录的研发基础设施。该仓库旨在提供关于标本、分类群、地点、出版物、历史资料、数字资源及未解研究问题的透明、可更新、可引用的记录。Mascarene Paleo is a developing research infrastructure for documenting the palaeontological and subfossil record of the Mascarene Islands. This repository is intended to provide a transparent, updateable, and citable record of specimens, taxa, localities, publications, historical sources, digital resources, and unresolved research questions. 文献发现 选题与研究问题 数据与向量库 0 ★ 122 manoj-bishwakarma/research_paper_recommendation_system 基于机器学习的 Python 推荐系统。Machine Learning Based Recommendation System in Python 文献发现 论文推荐与学术图谱 写作 工程化 Python 0 ★ 123 lunxkoe/meeting-based-research-paper-recommendation-system 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 Java 0 ★ 124 LuizDerkcz/AgentPanel 促成深度协作讨论，让 AI Agent 与人类共同探索跨学科复杂研究问题。Facilitate in-depth collaborative discussions where AI agents and humans explore complex research questions across disciplines. 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 125 Luckysingh22-stack/Research-Paper-Recommendation-and-Subject-Area-Prediction 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 Jupyter Notebook 0 ★ 126 Lacenedihia/Google-Search-Ranking-Discoverability-Capstone 研究问题与暂定方向Research Question and Provisional Lane 文献发现 选题与研究问题 多模态 HTML 0 ★ 127 Kritisha57/FinHop FinHop 是专为机构股票分析打造的多跳金融研究助手。它摄取 SEC 文件（10-K、10-Q），将其建模为时序感知、按公司组织的检索图，并回答需要跨多份文档、多家公司与多个财周期证据的对比与趋势类研究问题。FinHop is a multi-hop financial research assistant purpose-built for institutional equity analysis. It ingests SEC filings — 10-Ks, 10-Qs ,models them as a time-aware, company-aware retrieval graph, and answers comparative and trend-based research questions that require evidence from across multiple documents, companies, and fiscal periods. 文献发现 选题与研究问题 RAG 检索增强 0 ★ 128 krishaDevOps/strategic-data-exploration-planning Python 数据科学实习的战略数据探索规划项目，涵盖数据集选择、研究问题、数据清洗方法、探索性分析、统计技术、Python 工具及规划的分析流程Strategic data exploration planning project for a Data Science with Python internship, covering dataset selection, research questions, data cleaning methodology, exploratory analysis, statistical techniques, Python tools, and the planned analytical workflow. 文献发现 选题与研究问题 工程化 0 ★ 129 KhushiKhandelwal0001/Ai-Research-Agent 一个使用 OpenAI function calling 和 DuckDuckGo 搜索的网络搜索与研究问题回答 AI Agent。An AI agent that searches the web and answers research questions using OpenAI's function calling and DuckDuckGo search. 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 130 khaled-khurram/subaru-preglobal-icbm 适用于 preglobal 斯巴鲁车型带 EyeSight 的 ICBM（按键欺骗式 ACC 触发）— 已实车可用。全纵向控制仍是开放且未经证实的研究问题。ICBM (button-spoofed ACC actuation) for preglobal Subarus with EyeSight — live and working. Full longitudinal control is still an open, unproven research question. 文献发现 选题与研究问题 工程化 Python 0 ★ 131 Kevinornot/endnote-xml-literature-search 检索 EndNote XML 元数据，保守地匹配本地 PDF，并以可追溯的证据回答研究问题。Search EndNote XML metadata, conservatively match local PDFs, and answer research questions with traceable evidence. 文献发现 文献检索与全文获取 选题与研究问题 RAG 检索增强 Python 0 ★ 132 keerthana-kulal/tool-using-research-agent 一个使用工具的研究 agent，可搜索网页并以引文形式回答研究问题。A tool-using research agent that searches the web and answers research questions with citations. 文献发现 选题与研究问题 Agent 智能体 0 ★ 133 karanamabhinaysai-gif/A7_OSSP_PROJ 开发一个研究论文推荐系统，分析关键词、摘要、引用与用户兴趣以推荐相关论文。该系统使用图算法、相似度排序和优化技术，为研究者和学生提供个性化建议。Here's a version with **exactly 300 characters**: > Develop a research paper recommendation system that analyzes keywords, abstracts, citations, and user interests to recommend relevant papers. It uses graph algorithms, similarity ranking, and optimization techniques to deliver personalized suggestions for researchers and students. 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 HTML 0 ★ 134 juliusbai0228-stack/Paper-Recommendation-Agent 文献发现 论文推荐与学术图谱 写作 Agent 智能体 Python 0 ★ 135 jpabloglez/GenKG-Agent 基于 Neo4j 知识图谱回答生物医学研究问题的多 Agent 系统——采用 LangGraph 编排、图+向量混合 RAG、只读 Cypher 护栏、Docker 隔离的代码执行与人在环上审核。Multi-agent system answering biomedical research questions over a Neo4j knowledge graph — LangGraph orchestration, hybrid graph+vector RAG, read-only Cypher guardrails, Docker-isolated code execution and human-in-the-loop review 文献发现 选题与研究问题 论文推荐与学术图谱 Agent 智能体 Python 0 ★ 136 jetzlstorfer/podcaster 一个 multi-agent 流水线，将研究问题转换为可直接播放的播客——生成双主持人 MP3 以及 AI 生成的单集封面图 🎙️A multi-agent pipeline that turns a research question into a ready-to-play podcast — a two-host MP3 plus AI-generated episode cover art 🎙️ 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 137 Jaiswal-Akshay/Research-Paper-Assistant 基于本地 RAG 的 AI 研究助手，用于分析学术论文、总结研究发现、对比研究，并以页级引用回答研究问题。构建于 Python、Streamlit、Chroma、Sentence Transformers、Ollama 和 Llama 3。An AI research assistant using local RAG to analyze academic papers, summarize research findings, compare studies, and answer research questions with page-level citations. Built with Python, Streamlit, Chroma, Sentence Transformers, Ollama, and Llama 3. 文献发现 选题与研究问题 写作 RAG 检索增强 Python 0 ★ 138 ihek130/Research-Paper-Recommendation-System 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 Jupyter Notebook 0 ★ 139 hs99700-oss/UC-Dashboard-Construction 一个能回答我研究问题的 Dashboard。A Dashboard that answers my research questions 文献发现 选题与研究问题 工程化 0 ★ 140 hirsaeki/research-loom Research Loom 是 profile 驱动的 research harness，用于维持从研究问题与证据到发现、写作与发表的全链路可追溯性Research Loom is a profile-driven research harness for maintaining traceability from research questions and evidence through findings, writing, and publication. 文献发现 选题与研究问题 写作 评测基准 Python 0 ★ 141 hechp2199/research_agent 用于生物学研究问题的科学研究 Agent。Scientific Research Agent for biological research questions 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 142 harshitaganti6-cell/AI-Research-Assistant 集成 RAG、知识图谱、语义搜索、论文推荐与本地 LLMs 的 AI 研究助手AI Research Assistant with RAG, knowledge graphs, semantic search, paper recommendations, and local LLMs. 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 Python 0 ★ 143 Hamad-Alajeel/ApexQ4-Agent 基于 LangGraph 的 AI Agent，分析上市公司季度财报，利用 SEC 文件与结构化财务数据，帮助用户回答限定范围内的投研问题。A LangGraph-based AI agent that analyzes public company quarterly earnings reports and helps users answer a limited set of investment-research questions using SEC filings and structured financial data. 文献发现 选题与研究问题 Agent 智能体 Jupyter Notebook 0 ★ 144 gowthamsakelu/AegisAI-Autonomous-Research-Intelligence-Agent 一个真实场景下的多能力 AI Agent，可接收用户的研究问题，自主决策所需信息，调用工具/MCP，分析信息并产出结构化报告。A real world multi capability AI agent that can take a user's research question, decide what it needs, use tools/MCP, analyze information, and produce a structured report. 文献发现 选题与研究问题 MCP Agent 智能体 Python 0 ★