学术写作

145 Gaurav-portfolio/AI-Research-Paper-Recommendation-System AI 系统AI System 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 0 ★ 146 Garvit-Varshney20/AI-Research-Paper-Recommendation-System 基于 NLP 与语义嵌入（SciBERT/SPECTER）的 AI 论文推荐系统。用户输入论文或关键词，即可获得排序后的上下文相关推荐，解决关键词检索造成的信息过载，加速学术文献发现。An AI-powered system that recommends relevant research papers using NLP and semantic embeddings (SciBERT/SPECTER). Users input a paper or keywords and receive ranked, context-aware suggestions—solving information overload from keyword-based search and speeding up academic literature discovery. 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 0 ★ 147 FoundryNet/academic-intel-mcp 面向 AI Agent 的学术研究情报——论文检索、科学文献、引用分析、arXiv、作者指标、前沿研究与语义相关工作（pgvector）。支持 MCP + x402。Academic research intelligence for AI agents — paper search, scientific literature, citation analysis, arXiv, author metrics, trending research & semantic related-work (pgvector). MCP + x402. 文献发现 文献检索与全文获取 论文推荐与学术图谱系统综述 引用MCP写作 Agent 智能体 Python 0 ★ 148 Felicia123-prog/suriname-rainfall-analysis 苏里南降雨数据分析工具包：从多个气象站加载月度降雨总量，生成年度与多年降雨图，并产出回答苏里南气候、季节与降雨趋势关键研究问题的统计结果。A toolkit for analyzing rainfall data from Suriname. This project loads monthly rainfall totals from multiple weather stations, generates yearly and multi‑year rainfall graphs, and produces statistics that answer key research questions about Suriname’s climate, seasons, and rainfall trends. 文献发现 选题与研究问题 数据与统计分析 工程化 Python 0 ★ 149 ezer-k/chat_to_table 将真实世界的研究问题转化为带引用、可关联的 Snowflake 表。Turn real-world research questions into cited, joinable Snowflake tables. 文献发现 选题与研究问题 数据与向量库 Python 0 ★ 150 Evolved-Designs/dystiny-research-paths 为更好的 AI 研究问题梳理清晰的来源、主张、变更与权衡路径Calm source, claim, change, and tradeoff paths for better AI research questions 文献发现 选题与研究问题 Agent 智能体 HTML 0 ★ 151 evakonstantinova/ResearchIQ-Copilot ResearchIQ Copilot 是一款 AI 驱动的学术研究助手，允许用户与研究论文对话、生成文献综述、识别研究空白、对比方法论、发现经核验的同行评审研究，并将研究成果导出为 PDF 报告ResearchIQ Copilot is an AI-powered academic research assistant that allows users to chat with research papers, generate literature reviews, identify research gaps, compare methodologies, discover verified peer-reviewed studies, and export research outputs as PDF reports. 文献发现 选题与研究问题 系统综述研究设计与方法 PDF RAG 检索增强 Python 0 ★ 152 Elaine-764/Statistical-Properties-of-Financial-Market-Returns 研究问题：流动性金融资产的相关性与波动率随时间有多稳定？常用的高斯性质在真实市场数据中是否成立？Research Questions: How stable are correlations and volatility over time in liquid financial assets? Do commonly assumed Gaussian properties hold for real market data? 文献发现 选题与研究问题 评测基准 MATLAB 0 ★ 153 dxeledx/citesail 基于 Semantic Scholar 与 Crossref 的安全加固、双模式学术搜索工作台。A security-hardened, dual-mode scholarly search workbench powered by Semantic Scholar and Crossref. 文献发现 文献检索与全文获取 RAG 检索增强 JavaScript 0 ★ 154 drududuaomokaro/ScientiaPilot-Showcase ScientiaPilot 公开展示——从研究问题到发表全流程的科研出版操作系统。Public showcase for ScientiaPilot — a research publication operating system from research question to publication. 文献发现 选题与研究问题 Agent 智能体 0 ★ 155 DrSmriti159/scientific-research-assistant AI 辅助的科研工具，用于文献探索、证据抽取与研究问题结构化。An AI-assisted scientific research tool for exploring literature, extracting evidence, and structuring research questions. 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 156 dradhikac/ai-research-intelligence-platform 一个端到端的研究智能系统：摄取学术论文并进行语义理解，映射研究领域的关系与演进，探测尚未探索的研究空白，并使用多 Agent AI 流水线生成文献综述与回答研究问题——全部以纯 Python 构建。An end-to-end research intelligence system that ingests academic papers, understands them semantically, maps how research areas relate and evolve, detects unexplored research gaps, and uses a multi-agent AI pipeline to generate literature reviews and answer research questions — all built in pure Python. 文献发现 选题与研究问题 系统综述 Agent 智能体 Python 0 ★ 157 dg-vverma19/screen-time-impact-analysis- 使用 Kaggle 数据集分析屏幕时间对生产力多方面影响的研究问题This uses a dataset from Kaggle, to analyze multiple research questions on how screen time affects productivity in multiple aspects. 文献发现 选题与研究问题 工程化 HTML 0 ★ 158 deva2006923/Ai-research-paper-recommendation-engine 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 JavaScript 0 ★ 159 DataScienceEnthusiastic/Research_paper_recommendation 本项目根据用户检索与数据集中已有论文进行论文推荐This project recommends paper based upon your search and available papers inside the dataset 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 Python 0 ★ 160 DAShaikh10/ArXivFlow 智能研究论文推荐系统，聚合 ArXiv 与 Semantic Scholar 内容，简化学术发现流程。An intelligent research paper recommender system aggregating content from ArXiv and Semantic Scholar to streamline academic discovery. 文献发现 文献检索与全文获取 写作 RAG 检索增强 Python 0 ★ 161 d-e-c-d/AI_Articles_Scrapers 面向 arXiv 与 Semantic Scholar 的 Scrapy Spider，聚焦非洲 AI 生态 — 导出包含引用次数的丰富 CSV。Spiders Scrapy pour arXiv et Semantic Scholar, centrés sur l'écosystème IA africain — export CSV enrichi du nombre de citations. 文献发现 文献检索与全文获取 数据与向量库 Python 0 ★ 162 cool-develope/material-research 将研究压缩包转化为可搜索、可引用的素材。拆分为论文、代码与数据集，索引后即可提出 Deep Research 问题，并引用页码与源行。Self-hosted（Postgres、MinIO、Qdrant）。Turn research zips into searchable, citable materials. Split papers, code, and datasets; index them; ask Deep Research questions that cite pages and source lines. Self-hosted (Postgres, MinIO, Qdrant). 文献发现 选题与研究问题 数据与向量库 Python 0 ★ 163 ckirchoff17/research-question-builder 面向高中生设计的研究问题构建与行动计划开发工具Tool designed for high school students to build a research question and develop an action plan 文献发现 选题与研究问题 工程化 HTML 0 ★ 164 cikarahmanniaf/bangalore-restaurants-analysis 基于 Kaggle Zomato Bangalore 数据集的餐厅数据分析与可视化，涵盖数据预处理、探索性分析、研究问题与可视化。Restaurant data analysis and visualization using the Zomato Bangalore dataset from Kaggle, covering data preprocessing, exploratory analysis, research questions, and visualization. 文献发现 选题与研究问题 数据与统计分析 可视化 工程化 Jupyter Notebook 0 ★ 165 chaturvediaksh1304-sudo/substrate AI 研究助手：覆盖从研究问题到文献综合、研究空白识别、假设生成与实验设计。AI research assistant: research question to literature synthesis, gap detection, hypothesis generation, and experiment design. 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 166 Cefigueredo/information-retrieval 统一 9 种学术 API（PubMed、OpenAlex、arXiv、Semantic Scholar 等）的学术摘要获取器，以单一 Python 接口对外提供。Academic abstract fetcher unifying 9 scholarly APIs (PubMed, OpenAlex, arXiv, Semantic Scholar…) behind one Python interface 文献发现 文献检索与全文获取 RAG 检索增强 Python 0 ★ 167 camila-vieirao/article-analyzer AI 驱动的工具，根据特定研究问题分析文章并对其效用进行排序AI-powered tool that analyzes articles and ranks their utility based on a specific research question 文献发现 选题与研究问题 评测基准 0 ★ 168 byteshiftlabs/premise 多源科学与文献及数据集搜索引擎，作为 MCP server 为 AI Agent 提供服务。Multi-source scientific literature and dataset search engine, built as an MCP server for AI agents. 文献发现 文献检索与全文获取 论文推荐与学术图谱 MCP写作 Agent 智能体 Python 0 ★ 169 BluePinetree/MARS 从研究问题到论文——全自动化。基于多框架的机器学习研究流水线（CrewAI · AutoGen · LangGraph），支持流式 UI 与人在环控制。From a research question to a paper — automatically. Multi-framework ML research pipeline (CrewAI · AutoGen · LangGraph) with streaming UI and human-in-the-loop control. 文献发现 选题与研究问题 写作 Agent 智能体 Python 0 ★ 170 Bilalbaddi/scientific_paper_recommendation 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 Python 0 ★ 171 Atharv2122/Research-Paper-Ranking-Agent Research Paper Ranking Agent——用户向 Agent 提出研究问题，Agent 从 arXiv 检索学术论文，按相关性排序，并解释每篇论文排名的原因Research Paper Ranking Agent - a user gives the agent a research question, the agent retrieves academic papers from arXiv, ranks them according to relevance, and explains why each paper received its position. 文献发现 选题与研究问题 写作 Agent 智能体 Python 0 ★ 172 ashia-002/research-gap-discovery-agentic-orchestrator 多 Agent 研究编排框架，覆盖文献检索、论文分析、证据抽取、跨论文对比、知识综合与经过验证的研究空白发现。A multi-agent research orchestration framework for literature retrieval, paper analysis, evidence extraction, cross-paper comparison, knowledge synthesis, and validated research gap discovery. 文献发现 选题与研究问题 文献筛选与信息抽取 写作 Agent 智能体 Python 0 ★ 173 aseymourian/netflix-imdb-content-analytics 基于 IMDb 与 Netflix 互动数据（20K+ 匹配条目）的内容表现与受众分群分析。围绕五个研究问题，采用经校验的统计方法（bootstrap CI、k-means、卡方、Random Forest）作答——旨在展示面向 Disney DTC 的内容规划与分析能力。完整方法论与已知局限性均已记录。Content performance & audience segmentation analysis using IMDb and Netflix engagement data (20K+ matched titles). Five research questions answered with validated statistics (bootstrap CIs, k-means, chi-square, Random Forest) — built to demonstrate Content Planning & Analysis skills for Disney DTC. Full methodology + known limitations documented. 文献发现 选题与研究问题 数据与统计分析 工程化 Jupyter Notebook 0 ★ 174 aroojfatima-27/multi-agent-research-automation 基于 n8n 构建的多 Agent AI 研究助手——输入主题后自动规划研究问题、检索网络并生成完整报告；由 Groq (Llama 3.3) + Tavily 驱动Multi-agent AI research assistant built with n8n — takes a topic, plans research questions, searches the web and generates a full report automatically. Powered by Groq (Llama 3.3) + Tavily. 文献发现 选题与研究问题 Agent 智能体 0 ★ 175 archanakrishna44/ux-quant-researcher 分阶段的 AI 研究伙伴，辅助 UX 设计师从研究问题到独立可验证报告的完整流程。A staged AI research partner that takes a UX designer from research question to independently verified report. 文献发现 选题与研究问题 Agent 智能体 Python 0 ★ 176 api-evangelist/fintool Fintool — 由 API Evangelist 出品的公开 API 面的独立第三方档案。Fintool 是面向机构投资者（如对冲基金、资产管理人、买方与卖方分析师）的 AI 驱动权益研究分析师与金融副驾。其助手摄取 SEC 文件（10-K、10-Q、8-K）、财报电话会议记录及金Fintool — independent third-party profile of a public API surface, by API Evangelist. Fintool is an AI-powered equity research analyst and financial copilot built for institutional investors such as hedge funds, asset managers, and buy-side and sell-side analysts. Its assistant ingests SEC filings (10-K, 10-Q, 8-K), earnings-call transcripts, and f 文献发现 选题与研究问题 RAG 检索增强 0 ★ 177 AnningGao/arxiv_daily 基于个人研究兴趣的每日 arxiv 论文推荐，由 Claude 更新。Daily arxiv paper recommendation based on my research interest, updated by Claude. 文献发现 论文推荐与学术图谱 写作 RAG 检索增强 Python 0 ★ 178 ali-shehzan-punjwani/ali-shehzan-flyrank-ai-ml-internship 在 FlyRank AI 进行的机器学习工程实习工作，包含 ML 实验、研究问题、AI workflow 与应用机器学习项目。Machine Learning Engineering Internship work at FlyRank AI, including ML experiments, research questions, AI workflows, and applied machine learning projects. 文献发现 选题与研究问题 工程化 Jupyter Notebook 0 ★ 179 alexproductdesign/research-method-matrix 交互式矩阵：展示各类 UX 研究方法分别回答何种研究问题，覆盖 Discover/Design/Develop/Deploy 四个阶段。Interactive matrix: which UX research method answers which research question, across Discover/Design/Develop/Deploy. 文献发现 选题与研究问题 工程化 HTML 0 ★ 180 AJforge-dev/AI-Research-Agent 一个 agentic、循证的研究系统：通过工具调用、RAG 与显式的论据—来源核验从研究问题生成结构化、带引用的报告，避免盲目的 LLM 摘要；能识别来源冲突并如实报告不确定性An agentic, evidence-grounded research system that generates a structured, citation-backed report from a research question — using tool-calling, RAG, and explicit claim-to-source verification instead of blind LLM summarization. Detects conflicting sources and reports uncertainty rather than hiding it. 文献发现 选题与研究问题 引用 Agent 智能体 Python 0 ★