仓库/Skill 库

用于人工审阅 evidence-backed WAKG 文献抽取结果的临时公开预览。Temporary public preview for human review of evidence-backed WAKG literature extraction.

开源、原生支持 Claude 的文献综述工作流工具：支持 arXiv/DOI/URL/PDF 论文导入、章节抽取，并通过 paper-qa 实现单篇论文问答Open-source, Claude-native literature-review workflow tool: arXiv/DOI/URL/PDF paper ingest, section extraction, single-paper Q&A via paper-qa.

Agentic RAG：回答前对每条引用与原文进行核对，证据不足时弃答。具备自纠正检索循环、确定性引用锚定以及 prompt injection 防御能力。Agentic RAG that verifies every citation against source text before answering, and abstains when the evidence does not hold. Self-correcting retrieval loop, deterministic citation grounding, prompt-injection defence.

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

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.

FinVet v1 —— 用于金融虚假信息检测的 RAG 与外部事实核查（IEEE BigData 2025 workshop）。已被 danielberhane/finvet 取代。FinVet v1 — RAG and external fact-checking for financial misinformation detection (IEEE BigData 2025 workshop). Superseded by danielberhane/finvet

RAMR —— 检索增强记忆可靠性：面向 Agentic-RAG / 记忆系统的抗污染合成基准（附方法与发现）。RAMR — Retrieval-Augmented Memory Reliability: a contamination-resistant synthetic benchmark for agentic-RAG / memory systems (findings + method)

Download consensus ai，可在数秒内从科学论文中获取有证据支撑的答案。面向学生、临床工作者与好奇读者，Consensus 将复杂研究转化为清晰、带引用的洞察，是值得信赖的共识研究工具，助力更快文献综述与更明智决策。Download consensus ai to find evidence-backed answers from scientific papers in seconds. Built for students, clinicians, and curious readers, Consensus turns complex studies into clear insights with citations, making it a trusted consensus research tool for faster literature review and smarter decisions.

全球研究者的终极 AI 驱动发现平台。统一搜索 8+ 专业数据库（NCBI、arXiv、OpenAlex），结合 Llama 3.1 驱动的综合分析、RAG 问答与自动化文献综述。The ultimate AI-powered discovery hub for global researchers. Unified search across 8+ specialized portals (NCBI, arXiv, OpenAlex) with Llama 3.1-driven synthesis, RAG chat, and automated literature reviews.

Syx 是一个面向长周期项目与编码 Agent 的实验性本地 AI 记忆系统，探索主动上下文、日记忆滚动回收、睡眠式记忆整合、长期 RAG 检索、类梦境综合以及 markdown 记忆制品Syx is an experimental local AI memory system for long-running projects and coding agents. It explores active context, daily memory rolloff, sleep consolidation, long-term RAG retrieval, dream-like synthesis, and markdown memory artifacts.

综述论文 "From Representation Learning to Foundation Models" 的官方仓库。系统性地回顾了空间转录组学与病理学的多模态融合，提出三层分类法（嵌入、模型、知识层级）以及 2018 至 2026 年的演进路线图。Official repository for the survey "From Representation Learning to Foundation Models". A systematic review of multimodal fusion for Spatial Transcriptomics and Pathology, featuring a three-tier taxonomy (Embedding, Model, and Knowledge levels) and an evolutionary roadmap from 2018 to 2026.

钥石复盘：面向魔兽世界大秘境玩家的 AI 复盘教练（战术意图理解 + 社区知识库 RAG）

面向文献综述与历史学期刊策略的合规本地优先 Codex Skills。Rights-safe local-first Codex Skills for literature review and history journal strategy.

可审计的按需学术文献综述引擎Auditable on-demand academic literature review engine

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

基于 3,377 篇 arXiv 预印本的混合搜索与有依据问答，并附带若检索质量回退则失败 CI 的检索消融实验。Hybrid search and grounded question answering over 3,377 arXiv preprints — with a retrieval ablation that fails CI if quality regresses.

本地 LLM 基准测试、RAG、语音交互与 AI 助手Local LLM benchmarking, RAG, voice interaction and AI assistant

2026 掌握 LLM 搜索：完整的语义 AI 手册Master LLM Search in 2026: The Complete Semantic AI Handbook

为 LLM 记忆而构建。Built for LLMs memory

Uniphore 是一家企业级 AI 公司——"The Business AI Company"——成立于 2008 年，总部位于加利福尼亚州帕罗奥图。其旗舰平台 Business AI Cloud（BAIC）是一个主权化、可组合且安全的 AI 平台，分为四层：用于对企业数据进行零拷贝访问的 Data Layer、用于检索的 Knowledge Layer……Uniphore is an enterprise AI company — "The Business AI Company" — founded in 2008 and headquartered in Palo Alto, California. Its flagship platform, the Business AI Cloud (BAIC), is a sovereign, composable and secure AI platform organised into four layers: a Data Layer for zero-copy access to enterprise data, a Knowledge Layer for retrieval and…

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

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.

Hands-on 实验 2：基于合成技术语料构建 RAG pipeline，并通过沙箱化 NemoClaw agent 提供服务，附带 EN/VI 双语 GUI demo。Hands-on 2 lab: build a RAG pipeline over a synthetic technical corpus and serve it through a sandboxed NemoClaw agent, with a bilingual (EN/VI) GUI demo.

AI/RAG 平台蓝图，配备 Python 发布门控，覆盖路由、隐私、引用、向量恢复与离线证据验证。AI/RAG platform blueprint with Python release gates for routing, privacy, citations, vector recovery, and offline evidence validation.

通过分析 trace 诊断与调试 RAG 流水线，定位并修复影响答案质量与相关性的问题Diagnose and debug Retrieval Augmented Generation pipelines by analyzing traces to identify and fix issues affecting answer quality and relevance.

🌐 利用多跳图推理结合知识图谱和向量搜索，挖掘隐藏的全球供应链风险，获得更深层洞察。🌐 Map hidden global supply chain risks with multi-hop graph reasoning combining knowledge graphs and vector search for deeper insights.

AI 驱动的加密情绪日记——基于 RAG 的 LLM 反馈（TAIDE + ChromaDB）结合 Random Forest 情绪预测。Live demo：heartbox.tw（test1/test1）。AI-powered encrypted mood journal — RAG-grounded LLM feedback (TAIDE + ChromaDB) and Random Forest emotion forecasting. Live demo: heartbox.tw (test1/test1)

LLM 驱动的科学论文推荐系统LLM-driven scientific paper recommendation system

一个基于 C# 与本地 LLM 的学术论文 RAG（Retrieval-Augmented Generation）系统。目标是摄入研究论文语料，构建可回答文献综述类问题（如"其他论文关于 X 发现了什么"）的系统，回答严格基于真实源材料。A RAG (Retrieval-Augmented Generation) system for academic papers using C# and a local LLM. The goal is to ingest a corpus of research papers and build a system that can answer literature review questions like "what have other papers found about X"; grounded in the actual source material.

本仓库为关于肌少症 AI 驱动体形分析动态文献综述的源代码。通过自行修改配置文件，本仓库也可作为其他领域的模板使用。Store here are the source code for the dynamic Literature Review on AI-Driven Body Shape Analysis for Sarcopenia. You may also treat this repository as a template for other domains by configuring the configuration files by yourself.

提出研究问题，获得可核验的带引文报告Ask a research question, get a cited report you can check.

本地优先的印尼语字幕生成，面向授权学习资源。Local-first Indonesian caption generation for authorized learning sources

OncoRAG 是一个 RAG 系统，为临床医生和研究人员提供即时获取最新肿瘤学证据的能力——来源包括直接来自 PubMed 的随机对照试验、Meta 分析、系统综述和 III 期临床试验。提出临床问题，即可获得带引文的可靠答案。OncoRAG is a Retrieval-Augmented Generation system that gives clinicians and researchers instant access to the latest oncology evidence — drawing from Randomized Controlled Trials, Meta-Analyses, Systematic Reviews, and Phase III Clinical Trials sourced directly from PubMed. Ask a clinical question, get a grounded answer with citations.