为GPT/GLM等LLM大语言模型提供实用化交互接口,特别优化论文阅读/润色/写作体验,模块化设计,支持自定义快捷按钮&函数插件,支持Python和C++等项目剖析&自译解功能,PDF/LaTex论文翻译&总结功能,支持并行问询多种LLM模型,支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。
仓库/Skill 库
27 个 · LLM 基础设施 · 学术写作
精选的 LLM、AI 绘画等领域的教程和资源。Curated tutorials and resources for Large Language Models, AI Painting, 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。
面向 AI 辅助草稿的可读性与自然节奏改进的开源 pipeline 与参考实现。Open-source pipeline and reference implementations for improving the readability and natural cadence of AI-assisted drafts.
Prompt工程师指南,源自英文版,但增加了AIGC的prompt部分,为了降低同学们的学习门槛,翻译更新
OpenSkills:使用任意 LLM 在本地运行 Claude Skills。OpenSkills: Run Claude Skills Locally using any LLM
Google Deep Search 的实现,支持 1000+ 篇参考文献、本地推理、使用 RAPTOR 与抓取会话对话以及报告生成。An implementation of Google Deep Search with support for 1000+ references, local inference, chatting with your scraping session using RAPTOR, and report generation.
使用 GPT-3 辅助撰写基金申请书的实验Experiment to use GPT-3 to help write grant proposals.
A field-adaptive academic writing Skill for Chinese and English research papers. | 面向中英文学术论文的领域自适应写作 Skill。
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)
THIS PAPER IS FOR ENTERTAINMENT PURPOSES ONLY.この小説はフィクションであり、実在する団体または個人とは関係ありません。
一个可复用的 Codex Skill,用于证据对齐、AI 与人工审稿人就绪的学术写作。A reusable Codex skill for evidence-aligned, AI- and human-reviewer-ready academic writing.
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.
本代码库提供个人研究成果《Deep Learning Approach in Time Series Forecasting: Literature Review and Extension on Feature Extraction》的代码与报告存档。This repository provides code and report archive of individual research: Deep Learning Approach in Time Series Forecasting: Literature Review and Extension on Feature Extraction
贝叶斯统计研究语料库:面向贝叶斯统计(推断、计算、先验、模型选择、层次模型、非参数、深度贝叶斯、应用)的数据驱动、自动化校验文献综述Bayesian Statistics Research Corpus: Data-driven, auto-validated literature review for Bayesian statistics (inference, computation, priors, model selection, hierarchical, nonparametric, deep Bayesian, applications)
面向几何感知量子机器学习的可复现研究框架。A reproducible research framework for geometry-aware quantum machine learning.
本地优先、隐私至上的 AI 驱动学术写作人性化工具。AI-Powered Academic Writing Humanizer - Local-First, Privacy-Centric Solution
SILVA Networks 是一个 Python 包,提供扩展的深度均衡层、定点求解器、隐式微分、结构化算子、诊断工具以及可复现研究 notebook。SILVA Networks is a Python package for extended deep equilibrium layers, fixed-point solvers, implicit differentiation, structured operators, diagnostics, and reproducible research notebooks.
面向科学与医学写作的人性化润色的阿英双语 skill,同时保持学术准确性。Bilingual Arabic-English skill for humanizing scientific and medical writing while preserving scholarly accuracy.
Codex skill,面向交通运输与低空出行领域的学术写作(知识蒸馏自 LT)。Codex skill for transportation and low-altitude mobility academic writing (Knowledge distillation from LT)
基于仿真的 MRI 调度策略分析,结合统计分析与离散事件仿真,以优化资源利用率、等待时间、加班时长与患者吞吐量。Simulation-based analysis of MRI scheduling policies, combining statistical analysis and discrete-event simulation to optimize resource utilization, waiting times, overtime, and patient throughput.
基于 Torch2PC 的预测编码硕士论文可复现项目:在 Ubuntu/ROCm 上对 backpropagation 进行逐层与 compute-matched 对比,实现 PC-CATM/PC-TREF,对 state inference 进行机制诊断,并构建 QWake-PC 以实现自适应 exact inference —— 面向机制可解释的可复现预测编码研究。Воспроизводимый проект магистерской диссертации по predictive coding в Torch2PC: послойное и compute-matched сравнение с backpropagation, PC-CATM/PC-TREF, механизмная диагностика state inference и QWake-PC для адаптивного exact inference в Ubuntu/ROCm — reproducible research on mechanism-aware predictive coding.
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.
SLM-PICO-Screener 是用于自动化系统综述筛选的轻量 NLP 流水线,基于 Phi-3 Mini 配合 LoRA 与 4-bit 量化,将文章分类为 8 个 PICO 标签。体积约 90 MB,可在消费级 GPU/CPU 上运行,加速生物医学研究中的证据综合。SLM-PICO-Screener is a lightweight NLP pipeline automating systematic review screening. Built on Phi-3 Mini with LoRA & 4-bit quantization, it classifies articles into 8 PICO labels. At ~90 MB, it runs on consumer GPUs/CPU, accelerating evidence synthesis in biomedical research.