17 个 · 模型 · 学术写作
OpenMMLab 多模态高级生成与智能创作工具箱。释放魔力🪄：AIGC、易用 API、丰富模型库、扩散模型，支持文生图、图像/视频修复与增强等任务OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.
通过 CLI、Model Context Protocol (MCP) server 和 AI Agent Skill 编程访问 Gemini Notebook。Programmatic access to Gemini Notebook - via command-line interface (CLI), Model Context Protocol (MCP) server, and AI agent skills.
Zotero MCP：通过 Model Context Protocol 将你的 Zotero 研究库与 Claude 及其他 AI 助手连接，用于讨论论文、获取摘要、分析引用等。Zotero MCP: Connects your Zotero research library with Claude and other AI assistants via the Model Context Protocol to discuss papers, get summaries, analyze citations, and more.
Fengshenbang-LM(封神榜大模型)是IDEA研究院认知计算与自然语言研究中心主导的大模型开源体系，成为中文AIGC和认知智能的基础设施。
AI 音频数据集（AI-ADS）🎵，包含语音、音乐和音效，可为 Generative AI、AIGC、AI 模型训练、智能音频工具开发及音频应用提供训练数据。AI Audio Datasets (AI-ADS) 🎵, including Speech, Music, and Sound Effects, which can provide training data for Generative AI, AIGC, AI model training, intelligent audio tool development, and audio applications.
[CVPR2024 (Highlight)] RichDreamer：一种可泛化的法线-深度扩散模型，用于生成细节丰富的文本到 3D 内容。Live Demo：https://modelscope.cn/studios/Damo_XR_Lab/3D_AIGC[CVPR2024 (Highlight)] RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D. Live Demo：https://modelscope.cn/studios/Damo_XR_Lab/3D_AIGC
Model Context Protocol (MCP) 服务器的 Node.js 实现，支持从多源（包括 **Web of Science**、arXiv 等）搜索和下载学术论文。A Node.js implementation of the Model Context Protocol (MCP) server for searching and downloading academic papers from multiple sources, including **Web of Science**, arXiv, and more.
双模式 AI 研究工作空间：DeepSearch 在约 2 分钟内将查询转化为带引用的网络报告；Research Mode 运行 25 个 Agent 的流水线，撰写完整学术论文（含 PRISMA 流程图、经核验的引用，导出 PDF/DOCX）；设有 4 个人机协同检查点；基于 LangGraph、FastAPI 与任意 OpenAI 兼容 LLM 构建AI research workspace with two modes — DeepSearch turns a query into a cited web report in ~2 min; Research Mode runs a 25-agent pipeline that writes a full academic paper (PRISMA diagram, verified citations, PDF/DOCX export). 4 human-in-the-loop checkpoints. Built with LangGraph, FastAPI, and any OpenAI-compatible LLM.
Tox21 多终点毒性预测：可复现的研究与推理制品（冻结模型、FastAPI 服务、已审计的安全机制）Tox21 multi-endpoint toxicity prediction: a reproducible research and inference artifact (frozen model, FastAPI service, audited security)
面向生产环境的、有内存约束的跨模型 KV-cache 传输，具备受保护的回退机制与可复现研究工具链。Production-oriented, memory-bounded cross-model KV-cache transfer with guarded fallback and reproducible research tooling.
arXiv 论文的端到端推荐引擎：流式接入开放快照，使用量化 ONNX 模型对标题与摘要进行 embedding，构建 FAISS 向量索引，通过 FastAPI 服务提供推荐，并在 Streamlit 面板中交互探索。End-to-end recommendation engine for arXiv research papers: stream an open snapshot, embed titles + abstracts with a quantized ONNX model, build a FAISS vector index, serve recommendations through a FastAPI service, and explore them in a Streamlit dashboard.
可复现的研究流水线：将基于 Agent 的模型产出转化为有证据支撑的 LLM 高管报告。A reproducible research pipeline for converting agent-based model artifacts into evidence-backed LLM executive reports.
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.
基于 Transformer 架构的可复现研究原型，用于长周期建筑能耗预测，结合可微的热物理约束并支持跨建筑泛化A reproducible research prototype for long-horizon building energy forecasting using transformer architectures with differentiable thermal-physics constraints and cross-building generalization.
综述论文《From Representation Learning to Foundation Models》的官方仓库。系统综述空间转录组学与病理学的多模态融合，提出三层分类法（Embedding、Model、Knowledge 层级）及 2018 至 2025 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 2025.
RIFT — Race-state Inference From Telemetry。一项可复现研究实现，仅基于位置遥测重建具备事件感知的关联性比赛状态，涵盖路线进度、共享事件标识、检查点通过、物理顺序、前车关系、间距与间隔。RIFT — Race-state Inference From Telemetry. A reproducible research implementation for reconstructing occurrence-aware relational race state from positional telemetry alone, including route progress, shared occurrence identity, checkpoint crossings, physical order, car-ahead relations, gaps and intervals.
目标：将 State Space Models（SSM）/ Mamba 用于医学时间序列分析；总体研究问题：Mamba 模型能否提升基于步态信号检测帕金森病的分类模型性能: To use State Space Models (SSM)/ Mamba for medical time series analysis General research question: Can Mamba models improve the performance of classification models trained to detect Parkinson's disease using gait signals.