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Awesome-Awesome-LLMs

★ 33 Open GitHub ↗

🌟 The ultimate meta-collection of 200+ awesome LLM repositories

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# 🌟 Awesome-Awesome-LLMs 🌟

### *The Ultimate Meta-Collection for LLM Research Navigation*

[![Awesome](https://awesome.re/badge.svg)](https://awesome.re)
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[English](#) | [简体中文](#) | [日本語](#) | [한국어](#)

</div>

---

## 🎯 Vision & Mission

> **"Navigate the Ocean of LLM Research with a Lighthouse, Not a Compass"**

In the rapidly evolving landscape of Large Language Models, knowledge is scattered across thousands of repositories, papers, and resources. **Awesome-Awesome-LLMs** serves as your **meta-navigator** — a carefully curated directory of the most valuable "awesome lists" in the LLM ecosystem.

### 🚀 Our Vision

We envision a future where:
- 🔬 **Researchers** can instantly locate cutting-edge papers across 40+ specialized domains
- 👨‍💻 **Developers** can discover the best tools, frameworks, and implementations without drowning in noise
- 🎓 **Learners** can follow clear learning paths from fundamentals to advanced topics
- 🌍 **The Community** collaborates to keep the entire LLM knowledge ecosystem organized and accessible

### 💡 Why This Project Matters

**The Challenge:**
- 📈 LLM research papers grow exponentially (1000+ papers/month on arXiv)
- 🌊 Information overload makes it nearly impossible to stay current
- 🔍 Finding quality, categorized resources takes hours of manual searching
- 🧩 Knowledge is fragmented across hundreds of disconnected repositories

**Our Solution:**
- ✅ **One-Stop Meta-Index**: 200+ carefully vetted awesome lists covering every LLM domain
- ⭐ **Quality Ratings**: Each resource rated from ★☆☆☆☆ to ★★★★★ based on community value
- 🎯 **Precision Navigation**: 40+ fine-grained categories from training to deployment
- 🔄 **Living Document**: Continuously updated as new high-quality resources emerge
- 🌐 **Community-Driven**: Built by researchers, for researchers

### 📊 Project Statistics

| 📚 Categories | 🔗 Resources | ⭐ Total Stars | 📄 Papers Covered | 👥 Contributors |
|:------------:|:-----------:|:-------------:|:----------------:|:---------------:|
| **40+** | **200+** | **500K+** | **10,000+** | **Growing** |

</div>

### 🎁 What You'll Find Here

- 📖 **Pre-training & Post-training**: From foundational model training to RLHF and alignment
- 🖼️ **Multimodal LLMs**: Vision, audio, video understanding and generation
- 🤖 **Agents & RAG**: Autonomous systems and retrieval-augmented generation
- 🔧 **Infrastructure**: Training systems, inference optimization, deployment strategies
- 🎯 **Specialized Domains**: From medical AI to time series forecasting
- 🔒 **Safety & Security**: Robustness, interpretability, and ethical AI
- 📈 **Evaluation**: Benchmarks, metrics, and quality assessment frameworks
- 🌏 **Multilingual**: Chinese, Japanese, Korean, and more regional resources

---

## 🗺️ Quick Navigation Guide

### 🎯 Popular Starting Points

</div>

---

## Table of Contents

- [Topics](#topics)
  - [Training](#training)
  - [Multi-modal LLM](#multi-modal-llm)
  - [Reinforcement Learning](#reinforcement-learning)
  - [LLM Rec System](#llm-rec-system)
  - [Agent & RAG](#agent--rag)
  - [LLM Infra](#llm-infra)
  - [Deep Learning & Machine Learning](#deep-learning--machine-learning)
  - [LLM Courses & Books](#llm-courses--books)
  - [LLM Interview](#llm-interview)
  - [Chinese LLM & Domain Models](#chinese-llm--domain-models)
  - [LLM & NLP & Information Extraction](#llm--nlp--information-extraction)
  - [LLM & Big Data](#llm--big-data)
  - [LLM & Agents](#llm--agents)
  - [LLM & Knowledge Graph](#llm--knowledge-graph)
  - [LLM & RAG](#llm--rag)
  - [LLM Training Datasets](#llm-training-datasets)
  - [Code LLM](#code-llm)
  - [LLM Inference](#llm-inference)
  - [LLM Applications](#llm-applications)
  - [LLM Security & Robustness](#llm-security--robustness)
  - [LLM Interpretability](#llm-interpretability)
  - [LLM Reasoning](#llm-reasoning)
  - [LLM Compression & Long Context](#llm-compression--long-context)
  - [LLM Evaluation](#llm-evaluation)
  - [Small Language Models](#small-language-models)
  - [LLM & Time Series](#llm--time-series)
  - [LLM Survey](#llm-survey)
  - [LLM & Tables & Text2SQL](#llm--tables--text2sql)
  - [LLM & Document Intelligence](#llm--document-intelligence)
  - [Agent Frameworks](#agent-frameworks)
  - [Prompt Engineering](#prompt-engineering)
  - [Search & LLM](#search--llm)
  - [LLM Data Engineering](#llm-data-engineering)
  - [arXiv & Paper Tools](#arxiv--paper-tools)
  - [AI4Science & Scientific Discovery](#ai4science--scientific-discovery)
  - [MCP & Servers & Chinese Resources](#mcp--servers--chinese-resources)
  - [LLM Engineering & Monitoring](#llm-engineering--monitoring)
- [Contribution Guidelines](#contribution-guidelines)
- [Acknowledgments](#acknowledgments)
- [License](#license)

---

## 🎓 How to Use This Repository

### For Researchers 🔬
1. **Stay Current**: Check trending topics monthly to see what's hot
2. **Deep Dive**: Navigate to your specific research area (e.g., Reasoning, Multimodal)
3. **Follow Stars**: Higher-rated (★★★★★) repositories often contain seminal work
4. **Cross-Reference**: Many breakthroughs happen at intersections (e.g., RL + Multimodal)

### For Developers 👨‍💻
1. **Start with Applications**: Check [LLM Applications](#llm-applications) for real-world use cases
2. **Learn Infrastructure**: Explore [LLM Infra](#llm-infra) for deployment and optimization
3. **Build Agents**: Dive into [Agent Frameworks](#agent-frameworks) and [RAG](#llm--rag)
4. **Security First**: Don't miss [LLM Security](#llm-security--robustness)

### For Students 🎓
1. **Begin with Fundamentals**: Start from [Deep Learning & Machine Learning](#deep-learning--machine-learning)
2. **Follow Courses**: Check [LLM Courses & Books](#llm-courses--books)
3. **Practice**: Explore [Code LLM](#code-llm) for hands-on projects
4. **Prepare**: Visit [LLM Interview](#llm-interview) when job-hunting

### For Practitioners 💼
1. **Quick Solutions**: Jump to [Prompt Engineering](#prompt-engineering) for immediate impact
2. **Production Ready**: Explore [LLM Engineering & Monitoring](#llm-engineering--monitoring)
3. **Domain-Specific**: Find your industry in specialized sections
4. **Evaluation**: Master [LLM Evaluation](#llm-evaluation) for quality assurance

---

## 📋 Topics

### 🎓 Training
*Master the art of building LLMs from scratch*

| Direction   | GitHub Link                                                  | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| ----------- | ------------------------------------------------------------ | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| Pre-Train   | [RUCAIBox/awesome-llm-pretraining](https://github.com/RUCAIBox/awesome-llm-pretraining) ![](https://img.shields.io/github/stars/RUCAIBox/awesome-llm-pretraining.svg) | A curated list of awesome papers and resources for LLM pre-training |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Post-Train  | [mbzuai-oryx/Awesome-LLM-Post-training](https://github.com/mbzuai-oryx/Awesome-LLM-Post-training) ![](https://img.shields.io/github/stars/mbzuai-oryx/Awesome-LLM-Post-training.svg) | A curated list of awesome papers for LLM post-training |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Efficient Post-Train | [luo-junyu/Awesome-Data-Efficient-LLM](https://github.com/luo-junyu/Awesome-Data-Efficient-LLM) ![](https://img.shields.io/github/stars/luo-junyu/Awesome-Data-Efficient-LLM.svg) | Survey on efficient LLM training from data-centric perspectives | [arxiv:2510.25817](https://arxiv.org/pdf/2510.25817) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Chinese LLM | [lonePatient/awesome-pretrained-chinese-nlp-models](https://github.com/lonePatient/awesome-pretrained-chinese-nlp-models) ![](https://img.shields.io/github/stars/lonePatient/awesome-pretrained-chinese-nlp-models.svg) | A curated list of awesome Chinese NLP models |  | 💻Code+Models | ⭐⭐Intermediate | 🟡Stable | ★★★★☆     |

---

### 🎨 Multi-modal LLM
*Beyond text: Vision, audio, video, and cross-modal intelligence*

| Direction                   | GitHub Link                                                  | Description                                                  | Paper Link                                           | Content Type | Difficulty | Update Status | Rec Score |
| --------------------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ---------------------------------------------------- | ------------ | ---------- | ------------- | --------- |
| MLLM                        | [BradyFU/Awesome-Multimodal-Large-Language-Models](https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models) ![](https://img.shields.io/github/stars/BradyFU/Awesome-Multimodal-Large-Language-Models.svg) | Latest Papers and Datasets on Multimodal Large Language Models |                                                      | 📄Papers+📊Datasets | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Visual RL | [weijiawu/Awesome-Visual-Reinforcement-Learning](https://github.com/weijiawu/Awesome-Visual-Reinforcement-Learning) ![](https://img.shields.io/github/stars/weijiawu/Awesome-Visual-Reinforcement-Learning.svg) | 200+ works on RL in vision: multimodal LLMs, visual generation, VLA models | [arxiv:2508.08189](https://arxiv.org/pdf/2508.08189v1) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| RL+MLLM                     | [Sun-Haoyuan23/Awesome-RL-based-Reasoning-MLLMs](https://github.com/Sun-Haoyuan23/Awesome-RL-based-Reasoning-MLLMs) ![](https://img.shields.io/github/stars/Sun-Haoyuan23/Awesome-RL-based-Reasoning-MLLMs.svg) | Papers and resources on RL-based reasoning for MLLMs         |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| MLLM Reasoning              | [The-Martyr/Awesome-Multimodal-Reasoning](https://github.com/The-Martyr/Awesome-Multimodal-Reasoning) ![](https://img.shields.io/github/stars/The-Martyr/Awesome-Multimodal-Reasoning.svg) | Collection of papers and resources on multimodal reasoning   |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |
| VLA                         | [AoqunJin/Awesome-VLA-Post-Training](https://github.com/AoqunJin/Awesome-VLA-Post-Training) ![](https://img.shields.io/github/stars/AoqunJin/Awesome-VLA-Post-Training.svg) | Post-training methods for Vision-Language-Action models      |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |
| Computer Vision             | [jbhuang0604/awesome-computer-vision](https://github.com/jbhuang0604/awesome-computer-vision) ![](https://img.shields.io/github/stars/jbhuang0604/awesome-computer-vision.svg) | A curated list of awesome computer vision resources          |                                                      | 🔀Mixed | ⭐⭐Intermediate | 🟡Stable | ★★★★☆     |
| Video Understanding         | [yunlong10/Awesome-LLMs-for-Video-Understanding](https://github.com/yunlong10/Awesome-LLMs-for-Video-Understanding) ![](https://img.shields.io/github/stars/yunlong10/Awesome-LLMs-for-Video-Understanding.svg) | LLMs for video understanding and generation                  |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |
| Multimodal LLM              | [Atomic-man007/Awesome_Multimodel_LLM](https://github.com/Atomic-man007/Awesome_Multimodel_LLM) ![](https://img.shields.io/github/stars/Atomic-man007/Awesome_Multimodel_LLM.svg) | Comprehensive multimodal LLM resources                       |                                                      | 🔀Mixed | ⭐⭐Intermediate | 🟢Active | ★★★★☆     |
| Audio Models                | [EmulationAl/awesome-large-audio-models](https://github.com/EmulationAI/awesome-large-audio-models) ![](https://img.shields.io/github/stars/EmulationAI/awesome-large-audio-models.svg) | Large audio models and related resources                     |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |
| Multimodal LLM              | [HenryHZY/Awesome-Multimodal-LLM](https://github.com/HenryHZY/Awesome-Multimodal-LLM) ![](https://img.shields.io/github/stars/HenryHZY/Awesome-Multimodal-LLM.svg) | Multimodal large language models collection                  |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |
| Multimodal Reasoning        | [HITsz-TMG/Awesome-Large-Multimodal-Reasoning-Models](https://github.com/HITsz-TMG/Awesome-Large-Multimodal-Reasoning-Models) ![](https://img.shields.io/github/stars/HITsz-TMG/Awesome-Large-Multimodal-Reasoning-Models.svg) | Collection of large multimodal reasoning models              |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |
| Think With Images           | [zhaochen0110/Awesome_Think_With_Images](https://github.com/zhaochen0110/Awesome_Think_With_Images) ![](https://img.shields.io/github/stars/zhaochen0110/Awesome_Think_With_Images.svg) | Multimodal reasoning with images                             | [arxiv:2506.23918](https://arxiv.org/pdf/2506.23918) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| SpeechLM Survey             | [dreamtheater123/Awesome-SpeechLM-Survey](https://github.com/dreamtheater123/Awesome-SpeechLM-Survey) ![](https://img.shields.io/github/stars/dreamtheater123/Awesome-SpeechLM-Survey.svg) | Survey of speech language models, datasets, benchmarks       |                                                      | 📄Papers+📊Datasets | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| MLLM Segmentation           | [mc-lan/Awesome-MLLM-Segmentation](https://github.com/mc-lan/Awesome-MLLM-Segmentation) ![](https://img.shields.io/github/stars/mc-lan/Awesome-MLLM-Segmentation.svg) | Multimodal LLMs for image/video segmentation                 |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Medical VLMs                | [lab-rasool/Awesome-Medical-VLMs-and-Datasets](https://github.com/lab-rasool/Awesome-Medical-VLMs-and-Datasets) ![](https://img.shields.io/github/stars/lab-rasool/Awesome-Medical-VLMs-and-Datasets.svg) | Medical vision-language models and datasets                  |                                                      | 📄Papers+📊Datasets | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Multimodal Memory           | [patrick-tssn/Awesome-Multimodal-Memory](https://github.com/patrick-tssn/Awesome-Multimodal-Memory) ![](https://img.shields.io/github/stars/patrick-tssn/Awesome-Multimodal-Memory.svg) | Multimodal memory-augmented models                           |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Multimodal LLM for Code     | [xjywhu/Awesome-Multimodal-LLM-for-Code](https://github.com/xjywhu/Awesome-Multimodal-LLM-for-Code) ![](https://img.shields.io/github/stars/xjywhu/Awesome-Multimodal-LLM-for-Code.svg) | Multimodal LLMs for code generation                          |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Embodied VLA/VLN            | [jonyzhang2023/awesome-embodied-vla-va-vln](https://github.com/jonyzhang2023/awesome-embodied-vla-va-vln) ![](https://img.shields.io/github/stars/jonyzhang2023/awesome-embodied-vla-va-vln.svg) | Embodied vision-language-action and navigation               |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Multimodal Chain-of-Thought | [yaotingwangofficial/Awesome-MCoT](https://github.com/yaotingwangofficial/Awesome-MCoT)  ![](https://img.shields.io/github/stars/yaotingwangofficial/Awesome-MCoT.svg) | Multimodal chain-of-thought reasoning                        |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |

---

### 🎮 Reinforcement Learning
*Training intelligent agents through trial and reward*

| Direction              | GitHub Link                                                                                                                                                                                   | Description                                                                 | Paper Link                                           | Content Type | Difficulty  | Update Status | Rec Score |
| ---------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------- | ---------------------------------------------------- | ------------ | ----------- | ------------- | --------- |
| Reasoning with RL      | [TsinghuaC3I/Awesome-RL-Reasoning-Recipes](https://github.com/TsinghuaC3I/Awesome-RL-Reasoning-Recipes) ![](https://img.shields.io/github/stars/TsinghuaC3I/Awesome-RL-Reasoning-Recipes.svg) | Reasoning recipes with reinforcement learning                               |                                                      | 📄Papers     | ⭐⭐⭐Advanced | 🟢Active      | ★★★★★     |
| Agentic RL             | [xhyumiracle/Awesome-AgenticLLM-RL-Papers](https://github.com/xhyumiracle/Awesome-AgenticLLM-RL-Papers) ![](https://img.shields.io/github/stars/xhyumiracle/Awesome-AgenticLLM-RL-Papers.svg) | Survey of agentic reinforcement learning for LLMs with 500+ research papers | [arxiv:2509.02547](https://arxiv.org/pdf/2509.02547) | 📄Papers     | ⭐⭐⭐Advanced | 🟢Active      | ★★★★★     |
| RLVR                   | [smiles724/Awesome-LLM-RLVR](https://github.com/smiles724/Awesome-LLM-RLVR) ![](https://img.shields.io/github/stars/smiles724/Awesome-LLM-RLVR.svg)                                           | Reinforcement learning from visual reasoning                                |                                                      | 📄Papers     | ⭐⭐⭐Advanced | 🟢Active      | ★★★★★     |
| Deep Research          | [0russwest0/Awesome-Agent-RL](https://github.com/0russwest0/Awesome-Agent-RL?tab=readme-ov-file) ![](https://img.shields.io/github/stars/0russwest0/Awesome-Agent-RL.svg)                     | Deep research on agent-based reinforcement learning                         |                                                      | 📄Papers     | ⭐⭐⭐Advanced | 🟢Active      | ★★★★★     |

---

### 🛍️ LLM Rec System
*Personalized recommendations powered by language understanding*

| Direction                 | GitHub Link                                                  | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| ------------------------- | ------------------------------------------------------------ | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| LLM Rec Papers            | [nancheng58/Awesome-LLM4RS-Papers](https://github.com/nancheng58/Awesome-LLM4RS-Papers) ![](https://img.shields.io/github/stars/nancheng58/Awesome-LLM4RS-Papers.svg) | Papers on LLM for recommender systems |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| LLM Rec Papers & Projects | [CHIANGEL/Awesome-LLM-for-RecSys](https://github.com/CHIANGEL/Awesome-LLM-for-RecSys) ![](https://img.shields.io/github/stars/CHIANGEL/Awesome-LLM-for-RecSys.svg) | LLM for recommendation systems papers and projects |  | 📄Papers+💻Code | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| LLM4Rec Papers           | [WLiK/LLM4Rec-Awesome-Papers](https://github.com/WLiK/LLM4Rec-Awesome-Papers) ![](https://img.shields.io/github/stars/WLiK/LLM4Rec-Awesome-Papers.svg) | Awesome papers on LLM for recommendation |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |

---

### 🤖 Agent & RAG
*Autonomous systems enhanced with retrieval-augmented generation*

| Direction       | GitHub Link                                                                                                                                                               | Description                                                | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------- | ---------- | ------------ | ---------- | ------------- | --------- |
| AI agents & RAG | [Shubhamsaboo/awesome-llm-apps](https://github.com/Shubhamsaboo/awesome-llm-apps) ![](https://img.shields.io/github/stars/Shubhamsaboo/awesome-llm-apps.svg)              | Collection of awesome LLM applications with agents and RAG |            | 💻Code+📚Tutorials | ⭐⭐Intermediate | 🟢Active | ★★★★★     |
| Deep Research   | [0russwest0/Awesome-Agent-RL](https://github.com/0russwest0/Awesome-Agent-RL?tab=readme-ov-file) ![](https://img.shields.io/github/stars/0russwest0/Awesome-Agent-RL.svg) | Deep research on agent-based reinforcement learning        |            | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| GraphRAG        | [DEEP-PolyU/Awesome-GraphRAG](https://github.com/DEEP-PolyU/Awesome-GraphRAG) ![](https://img.shields.io/github/stars/DEEP-PolyU/Awesome-GraphRAG.svg)                    | A curated list of papers and resources on GraphRAG         |            | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |

---

### ⚙️ LLM Infra
*Infrastructure, systems, and optimization for production deployment*

| Direction            | GitHub Link                                                  | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| -------------------- | ------------------------------------------------------------ | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| Efficient Architecture | [weigao266/Awesome-Efficient-Arch](https://github.com/weigao266/Awesome-Efficient-Arch) ![](https://img.shields.io/github/stars/weigao266/Awesome-Efficient-Arch.svg) | Survey on efficient architectures: linear attention, sparse attention, MoE, hybrid models | [arxiv:2508.09834](https://arxiv.org/pdf/2508.09834) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| LLM Inference        | [xlite-dev/Awesome-LLM-Inference](https://github.com/xlite-dev/Awesome-LLM-Inference) ![](https://img.shields.io/github/stars/xlite-dev/Awesome-LLM-Inference.svg) | Comprehensive resources for LLM inference optimization |  | 📄Papers+🛠️Tools | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Speculative decoding | [hemingkx/SpeculativeDecodingPapers](https://github.com/hemingkx/SpeculativeDecodingPapers) ![](https://img.shields.io/github/stars/hemingkx/SpeculativeDecodingPapers.svg) | Collection of papers on speculative decoding |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Training System      | [InternLM/Awesome-LLM-Training-System](https://github.com/InternLM/Awesome-LLM-Training-System?tab=readme-ov-file) ![](https://img.shields.io/github/stars/InternLM/Awesome-LLM-Training-System.svg) | Resources for LLM training systems and infrastructure |  | 📄Papers+🛠️Tools | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |
| Training/Inference   | [AmadeusChan/Awesome-LLM-System-Papers](https://github.com/AmadeusChan/Awesome-LLM-System-Papers) ![](https://img.shields.io/github/stars/AmadeusChan/Awesome-LLM-System-Papers.svg) | Papers on LLM training and inference systems |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |

---

### 🧠 Deep Learning & Machine Learning
*Foundation of modern AI - the building blocks of LLMs*

| Direction | GitHub Link | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------- | ----------- | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| Deep Learning | [ChristosChristofidis/awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) ![](https://img.shields.io/github/stars/ChristosChristofidis/awesome-deep-learning.svg) | A curated list of awesome Deep Learning tutorials, projects and communities |  | 🔀Mixed | ⭐Beginner | 🟡Stable | ★★★★★ |
| Machine Learning | [josephmisiti/awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning) ![](https://img.shields.io/github/stars/josephmisiti/awesome-machine-learning.svg) | A curated list of awesome Machine Learning frameworks, libraries and software |  | 🔀Mixed | ⭐Beginner | 🟡Stable | ★★★★★ |
| Deep Learning Papers | [terryum/awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers) ![](https://img.shields.io/github/stars/terryum/awesome-deep-learning-papers.svg) | The most cited deep learning papers |  | 📄Papers | ⭐⭐Intermediate | 🟡Stable | ★★★★☆ |

---

### 📚 LLM Courses & Books
*Structured learning materials to master LLM technology*

---

### 💼 LLM Interview
*Ace your AI/ML interviews with confidence*

| Direction | GitHub Link | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------- | ----------- | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| Interview Questions | [DopplerHQ/awesome-interview-questions](https://github.com/DopplerHQ/awesome-interview-questions) ![](https://img.shields.io/github/stars/DopplerHQ/awesome-interview-questions.svg) | A curated list of lists of technical interview questions |  | 📚Resources | ⭐⭐Intermediate | 🟡Stable | ★★★★★ |
| CV | [posquit0/Awesome-CV](https://github.com/posquit0/Awesome-CV) ![](https://img.shields.io/github/stars/posquit0/Awesome-CV.svg) | LaTeX template for your outstanding job application |  | 🛠️Tools | ⭐Beginner | 🟡Stable | ★★★★☆ |
| LLM Interview Notes | [jackaduma/awesome_LLMs_interview_notes](https://github.com/jackaduma/awesome_LLMs_interview_notes) ![](https://img.shields.io/github/stars/jackaduma/awesome_LLMs_interview_notes.svg) | Collection of LLM interview preparation notes and resources |  | 📚Resources | ⭐⭐Intermediate | 🟢Active | ★★★★☆ |
| Deep Learning Interview | [315386775/DeepLearing-Interview-Awesome-2024](https://github.com/315386775/DeepLearing-Interview-Awesome-2024) ![](https://img.shields.io/github/stars/315386775/DeepLearing-Interview-Awesome-2024.svg) | Deep learning interview questions and answers for 2024 |  | 📚Resources | ⭐⭐Intermediate | 🟢Active | ★★★★☆ |

---

### 🇨🇳 Chinese LLM & Domain Models
*Specialized models for Chinese language and specific domains*

---

### 📝 LLM & NLP & Information Extraction
*Natural language processing and structured information extraction*

---

### 💾 LLM & Big Data
*Scaling LLMs with big data frameworks and technologies*

---

### 🦾 LLM & Agents
*Autonomous AI agents powered by language models*

| Direction | GitHub Link | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------- | ----------- | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| GPT Agents | [fr0gger/Awesome-GPT-Agents](https://github.com/fr0gger/Awesome-GPT-Agents) ![](https://img.shields.io/github/stars/fr0gger/Awesome-GPT-Agents.svg) | A curated list of GPT agents and resources |  | 🔀Mixed | ⭐⭐Intermediate | 🟢Active | ★★★★★ |
| LLM Powered Agent | [hyp1231/awesome-llm-powered-agent](https://github.com/hyp1231/awesome-llm-powered-agent) ![](https://img.shields.io/github/stars/hyp1231/awesome-llm-powered-agent.svg) | Collection of LLM-powered autonomous agents |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| Self-Evolving Agents | [EvoAgentX/Awesome-Self-Evolving-Agents](https://github.com/EvoAgentX/Awesome-Self-Evolving-Agents) ![](https://img.shields.io/github/stars/EvoAgentX/Awesome-Self-Evolving-Agents.svg) | Survey on self-evolving AI agents with prompt, memory, and tool optimization | [alphaxiv:2508.07407](https://www.alphaxiv.org/abs/2508.07407) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| Data Agents | [HKUSTDial/awesome-data-agents](https://github.com/HKUSTDial/awesome-data-agents) ![](https://img.shields.io/github/stars/HKUSTDial/awesome-data-agents.svg) | Survey of data agents across data lifecycle with autonomy levels (L0-L3) | [arxiv:2510.23587](https://arxiv.org/pdf/2510.23587) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| LLM Robotics | [GT-RIPL/Awesome-LLM-Robotics](https://github.com/GT-RIPL/Awesome-LLM-Robotics) ![](https://img.shields.io/github/stars/GT-RIPL/Awesome-LLM-Robotics.svg) | Resources for LLM applications in robotics |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| Embodied Agent | [zchoi/Awesome-Embodied-Agent-with-LLMs](https://github.com/zchoi/Awesome-Embodied-Agent-with-LLMs) ![](https://img.shields.io/github/stars/zchoi/Awesome-Embodied-Agent-with-LLMs.svg) | Resources for embodied agents powered by LLMs |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| LLM Agents | [kaushikb11/awesome-llm-agents](https://github.com/kaushikb11/awesome-llm-agents) ![](https://img.shields.io/github/stars/kaushikb11/awesome-llm-agents.svg) | Comprehensive collection of LLM-based agents |  | 🔀Mixed | ⭐⭐Intermediate | 🟢Active | ★★★★★ |
| AI Agents | [e2b-dev/awesome-ai-agents](https://github.com/e2b-dev/awesome-ai-agents) ![](https://img.shields.io/github/stars/e2b-dev/awesome-ai-agents.svg) | A curated list of AI agents and frameworks |  | 🛠️Tools+Frameworks | ⭐⭐Intermediate | 🟢Active | ★★★★★ |

---

### 🕸️ LLM & Knowledge Graph
*Enhancing LLMs with structured knowledge*

---

### 🔍 LLM & RAG
*Retrieval-Augmented Generation for knowledge-enhanced LLMs*

| Direction | GitHub Link | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------- | ----------- | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| LLM RAG | [jxzhangjhu/Awesome-LLM-RAG](https://github.com/jxzhangjhu/Awesome-LLM-RAG) ![](https://img.shields.io/github/stars/jxzhangjhu/Awesome-LLM-RAG.svg) | Comprehensive resources for Retrieval-Augmented Generation |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| RAG Top Conferences | [liunian-Jay/Awesome-RAG](https://github.com/liunian-Jay/Awesome-RAG) ![](https://img.shields.io/github/stars/liunian-Jay/Awesome-RAG.svg) | RAG papers from ACL, ICML, ICLR, EMNLP, NeurIPS 2024-2025 |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| RAG Application | [lizhe2004/Awesome-LLM-RAG-Application](https://github.com/lizhe2004/Awesome-LLM-RAG-Application) ![](https://img.shields.io/github/stars/lizhe2004/Awesome-LLM-RAG-Application.svg) | Collection of practical RAG applications with LLMs |  | 💻Code+📚Tutorials | ⭐⭐Intermediate | 🟢Active | ★★★★★ |
| RAG Survey | [hymie122/RAG-Survey](https://github.com/hymie122/RAG-Survey) ![](https://img.shields.io/github/stars/hymie122/RAG-Survey.svg) | Comprehensive survey of RAG techniques and papers |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| RAG Papers | [gomate-community/awesome-papers-for-rag](https://github.com/gomate-community/awesome-papers-for-rag) ![](https://img.shields.io/github/stars/gomate-community/awesome-papers-for-rag.svg) | Curated collection of research papers on RAG |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| RAG Evaluation | [YHPeter/Awesome-RAG-Evaluation](https://github.com/YHPeter/Awesome-RAG-Evaluation) ![](https://img.shields.io/github/stars/YHPeter/Awesome-RAG-Evaluation.svg) | Resources for evaluating RAG systems |  | 📄Papers+🛠️Tools | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| RAG | [ethan-funny/awesome-rag](https://github.com/ethan-funny/awesome-rag/tree/main) ![](https://img.shields.io/github/stars/ethan-funny/awesome-rag.svg) | General resources and tools for RAG |  | 🔀Mixed | ⭐⭐Intermediate | 🟢Active | ★★★★☆ |
| Personalized RAG Agent | [Applied-Machine-Learning-Lab/Awesome-Personalized-RAG-Agent](https://github.com/Applied-Machine-Learning-Lab/Awesome-Personalized-RAG-Agent) ![](https://img.shields.io/github/stars/Applied-Machine-Learning-Lab/Awesome-Personalized-RAG-Agent.svg) | Personalized RAG and agent techniques |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| RAG Vision | [zhengxuJosh/Awesome-RAG-Vision](https://github.com/zhengxuJosh/Awesome-RAG-Vision) ![](https://img.shields.io/github/stars/zhengxuJosh/Awesome-RAG-Vision.svg) | RAG in computer vision |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| Awesome-RAG | [Danielskry/Awesome-RAG](https://github.com/Danielskry/Awesome-RAG) ![](https://img.shields.io/github/stars/Danielskry/Awesome-RAG.svg) | General RAG resources and techniques |  | 🔀Mixed | ⭐⭐Intermediate | 🟢Active | ★★★★★ |

---

### 📊 LLM Training Datasets
*High-quality datasets for pre-training and fine-tuning*

| Direction           | GitHub Link                                                                                                                                                                       | Description                                            | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------ | ---------- | ------------ | ---------- | ------------- | --------- |
| LLM Datasets        | [lmmlzn/Awesome-LLMs-Datasets](https://github.com/lmmlzn/Awesome-LLMs-Datasets) ![](https://img.shields.io/github/stars/lmmlzn/Awesome-LLMs-Datasets.svg)                         | Comprehensive collection of datasets for training LLMs |            | 📊Datasets | ⭐⭐Intermediate | 🟢Active | ★★★★★     |
| Instruction Dataset | [yaodongC/awesome-instruction-dataset](https://github.com/yaodongC/awesome-instruction-dataset) ![](https://img.shields.io/github/stars/yaodongC/awesome-instruction-dataset.svg) | Collection of instruction-tuning datasets for LLMs     |            | 📊Datasets | ⭐⭐Intermediate | 🟢Active | ★★★★★     |
| ChatGPT Dataset     | [voidful/awesome-chatgpt-dataset](https://github.com/voidful/awesome-chatgpt-dataset) ![](https://img.shields.io/github/stars/voidful/awesome-chatgpt-dataset.svg)                | Datasets specifically curated for ChatGPT-like models  |            | 📊Datasets | ⭐⭐Intermediate | 🟡Stable | ★★★★☆     |

---

### 🔧 LLM Data Engineering
*Data pipelines and engineering practices for LLM workflows*

---

### 💻 Code LLM
*Large language models for code generation and understanding*

---

### ⚡ LLM Inference
*Optimization techniques for faster and more efficient LLM inference*

| Direction              | GitHub Link                                                                                                                                                                                                  | Description                                    | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------- | ---------- | ------------ | ---------- | ------------- | --------- |
| Efficient LLM          | [horseee/Awesome-Efficient-LLM](https://github.com/horseee/Awesome-Efficient-LLM) ![](https://img.shields.io/github/stars/horseee/Awesome-Efficient-LLM.svg)                                                 | Methods and tools for efficient LLM deployment |            | 📄Papers+🛠️Tools | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Knowledge Distillation | [Tebmer/Awesome-Knowledge-Distillation-of-LLMs](https://github.com/Tebmer/Awesome-Knowledge-Distillation-of-LLMs) ![](https://img.shields.io/github/stars/Tebmer/Awesome-Knowledge-Distillation-of-LLMs.svg) | Resources for LLM knowledge distillation       |            | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| System2 Reasoning      | [zzli2022/Awesome-System2-Reasoning-LLM](https://github.com/zzli2022/Awesome-System2-Reasoning-LLM) ![](https://img.shields.io/github/stars/zzli2022/Awesome-System2-Reasoning-LLM.svg)                      | Research on System 2 reasoning in LLMs         |            | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |

---

### 🚀 LLM Applications
*Real-world applications and production-ready LLM solutions*

| Direction  | GitHub Link                                                                                                                                                  | Description                                                | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------- | ---------- | ------------ | ---------- | ------------- | --------- |
| LLM        | [Hannibal046/Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM) ![](https://img.shields.io/github/stars/Hannibal046/Awesome-LLM.svg)                   | Comprehensive collection of LLM resources and applications |            | 🔀Mixed | ⭐⭐Intermediate | 🟢Active | ★★★★★     |
| LLMOps     | [tensorchord/Awesome-LLMOps](https://github.com/tensorchord/Awesome-LLMOps) ![](https://img.shields.io/github/stars/tensorchord/Awesome-LLMOps.svg)          | Resources for LLM operations and deployment                |            | 🛠️Tools | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| AI Tools   | [ikaijua/Awesome-AITools](https://github.com/ikaijua/Awesome-AITools) ![](https://img.shields.io/github/stars/ikaijua/Awesome-AITools.svg)                   | Curated list of AI tools and applications                  |            | 🛠️Tools | ⭐Beginner | 🟢Active | ★★★★★     |
| LLM Web UI | [JShollaj/awesome-llm-web-ui](https://github.com/JShollaj/awesome-llm-web-ui) ![](https://img.shields.io/github/stars/JShollaj/awesome-llm-web-ui.svg)       | Web interfaces and UIs for LLM applications                |            | 🛠️Tools | ⭐⭐Intermediate | 🟢Active | ★★★★☆     |

---

### 🔐 LLM Security & Robustness
*Protecting LLMs from attacks and ensuring reliability*

---

### 🔬 LLM Interpretability
*Understanding how LLMs work and make decisions*

| Direction | GitHub Link | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------- | ----------- | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| LLM Interpretability | [JShollaj/awesome-llm-interpretability](https://github.com/JShollaj/awesome-llm-interpretability) ![](https://img.shields.io/github/stars/JShollaj/awesome-llm-interpretability.svg) | Resources for understanding and interpreting LLM behavior |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |

---

### 🧩 LLM Reasoning
*Advanced reasoning capabilities - the frontier of LLM research*

| Direction                       | GitHub Link                                                                                                                                                                                                        | Description                                                 | Paper Link                                           | Content Type | Difficulty | Update Status | Rec Score |
| ------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------- | ---------------------------------------------------- | ------------ | ---------- | ------------- | --------- |
| LLM Reasoning                   | [atfortes/Awesome-LLM-Reasoning](https://github.com/atfortes/Awesome-LLM-Reasoning) ![](https://img.shields.io/github/stars/atfortes/Awesome-LLM-Reasoning.svg)                                                    | Collection of resources on LLM reasoning capabilities       |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| LLM Reasoning Resources         | [WangRongsheng/awesome-LLM-resourses](https://github.com/WangRongsheng/awesome-LLM-resourses) ![](https://img.shields.io/github/stars/WangRongsheng/awesome-LLM-resourses.svg)                                     | Comprehensive resources for LLMs and reasoning models       |                                                      | 🔀Mixed | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| LLM Engineer Toolkit            | [KalyanKS-NLP/llm-engineer-toolkit](https://github.com/KalyanKS-NLP/llm-engineer-toolkit) ![](https://img.shields.io/github/stars/KalyanKS-NLP/llm-engineer-toolkit.svg)                                           | Toolkit for LLM engineering and deployment                  |                                                      | 🛠️Tools | ⭐⭐Intermediate | 🟢Active | ★★★★★     |
| Long2short on LRMs              | [Hongcheng-Gao/Awesome-Long2short-on-LRMs](https://github.com/Hongcheng-Gao/Awesome-Long2short-on-LRMs) ![](https://img.shields.io/github/stars/Hongcheng-Gao/Awesome-Long2short-on-LRMs.svg)                      | Long text compression and efficient reasoning for LRMs      |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| MLLM Reasoning                  | [phellonchen/Awesome-MLLM-Reasoning](https://github.com/phellonchen/Awesome-MLLM-Reasoning) ![](https://img.shields.io/github/stars/phellonchen/Awesome-MLLM-Reasoning.svg)                                        | Multimodal LLM reasoning resources                          |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| RL-based Reasoning MLLMs        | [Sun-Haoyuan23/Awesome-RL-based-Reasoning-MLLMs](https://github.com/Sun-Haoyuan23/Awesome-RL-based-Reasoning-MLLMs) ![](https://img.shields.io/github/stars/Sun-Haoyuan23/Awesome-RL-based-Reasoning-MLLMs.svg)    | RL-based multimodal reasoning models                        |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Efficient Reasoning for LLMs    | [Eclipsess/Awesome-Efficient-Reasoning-LLMs](https://github.com/Eclipsess/Awesome-Efficient-Reasoning-LLMs) ![](https://img.shields.io/github/stars/Eclipsess/Awesome-Efficient-Reasoning-LLMs.svg)                | Survey on efficient reasoning for LLMs                      | [arxiv:2503.16419](https://arxiv.org/pdf/2503.16419) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| System2 Reasoning LLM           | [zzli2022/Awesome-System2-Reasoning-LLM](https://github.com/zzli2022/Awesome-System2-Reasoning-LLM) ![](https://img.shields.io/github/stars/zzli2022/Awesome-System2-Reasoning-LLM.svg)                            | System 1 to System 2 reasoning in LLMs                      | [arxiv:2502.17419](https://arxiv.org/pdf/2502.17419) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Efficient LRM Reasoning         | [XiaoYee/Awesome_Efficient_LRM_Reasoning](https://github.com/XiaoYee/Awesome_Efficient_LRM_Reasoning) ![](https://img.shields.io/github/stars/XiaoYee/Awesome_Efficient_LRM_Reasoning.svg)                         | Efficient reasoning for large reasoning models              | [arxiv:2503.21614](https://arxiv.org/pdf/2503.21614) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Efficient CoT Reasoning         | [Blueyee/Efficient-CoT-LRMs](https://github.com/Blueyee/Efficient-CoT-LRMs) ![](https://img.shields.io/github/stars/Blueyee/Efficient-CoT-LRMs.svg)                                                                | Efficient chain-of-thought reasoning                        |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Efficient CoT Reasoning Summary | [zwxandy/Awesome-Efficient-CoT-Reasoning-Summary](https://github.com/zwxandy/Awesome-Efficient-CoT-Reasoning-Summary) ![](https://img.shields.io/github/stars/zwxandy/Awesome-Efficient-CoT-Reasoning-Summary.svg) | CoT efficient reasoning summary                             |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Deep Reasoning                  | [modelscope/awesome-deep-reasoning](https://github.com/modelscope/awesome-deep-reasoning) ![](https://img.shields.io/github/stars/modelscope/awesome-deep-reasoning.svg)                                           | Deep reasoning models, datasets, and metrics                |                                                      | 📄Papers+📊Datasets | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Interleaving Reasoning          | [Osilly/Awesome-Interleaving-Reasoning](https://github.com/Osilly/Awesome-Interleaving-Reasoning) ![](https://img.shields.io/github/stars/Osilly/Awesome-Interleaving-Reasoning.svg)                               | Interleaving reasoning: multimodal, multi-agent, multi-turn |                                                      | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |

---

### 📦 LLM Compression & Long Context
*Making LLMs smaller, faster, and capable of processing longer contexts*

| Direction | GitHub Link | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------- | ----------- | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| Long Context Modeling | [Xnhyacinth/Awesome-LLM-Long-Context-Modeling](https://github.com/Xnhyacinth/Awesome-LLM-Long-Context-Modeling) ![](https://img.shields.io/github/stars/Xnhyacinth/Awesome-LLM-Long-Context-Modeling.svg) | Resources for handling long context in LLMs |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| LLM Compression | [HuangOwen/Awesome-LLM-Compression](https://github.com/HuangOwen/Awesome-LLM-Compression) ![](https://img.shields.io/github/stars/HuangOwen/Awesome-LLM-Compression.svg) | Methods and tools for compressing LLMs |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| Token-level Compression | [xuyang-liu16/Awesome-Token-level-Model-Compression](https://github.com/xuyang-liu16/Awesome-Token-level-Model-Compression) ![](https://img.shields.io/github/stars/xuyang-liu16/Awesome-Token-level-Model-Compression.svg) | Token-level model compression resources |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| LLM Ensemble | [junchenzhi/Awesome-LLM-Ensemble](https://github.com/junchenzhi/Awesome-LLM-Ensemble) ![](https://img.shields.io/github/stars/junchenzhi/Awesome-LLM-Ensemble.svg) | Survey on LLM ensemble methods | [arxiv:2502.18036](https://arxiv.org/abs/2502.18036) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| Model Merging | [EnnengYang/Awesome-Model-Merging-Methods-Theories-Applications](https://github.com/EnnengYang/Awesome-Model-Merging-Methods-Theories-Applications) ![](https://img.shields.io/github/stars/EnnengYang/Awesome-Model-Merging-Methods-Theories-Applications.svg) | Model merging methods, theories, and applications | [arxiv:2408.07666](https://arxiv.org/pdf/2408.07666) | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |

---

### 📏 LLM Evaluation
*Benchmarks, metrics, and methods for evaluating LLM performance*

| Direction | GitHub Link | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------- | ----------- | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| Hallucination Detection | [EdinburghNLP/awesome-hallucination-detection](https://github.com/EdinburghNLP/awesome-hallucination-detection) ![](https://img.shields.io/github/stars/EdinburghNLP/awesome-hallucination-detection.svg) | Resources for detecting and mitigating LLM hallucinations |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| LLM Evaluation Papers | [tjunlp-lab/Awesome-LLMs-Evaluation-Papers](https://github.com/tjunlp-lab/Awesome-LLMs-Evaluation-Papers) ![](https://img.shields.io/github/stars/tjunlp-lab/Awesome-LLMs-Evaluation-Papers.svg) | Collection of papers on LLM evaluation methods |  | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |
| LLM Eval | [onejune2018/Awesome-LLM-Eval](https://github.com/onejune2018/Awesome-LLM-Eval) ![](https://img.shields.io/github/stars/onejune2018/Awesome-LLM-Eval.svg) | Comprehensive resources for LLM evaluation |  | 📄Papers+🛠️Tools | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |

---

### 📱 Small Language Models
*Efficient, compact models for resource-constrained environments*

---

### 📈 LLM & Time Series
*Applying language models to temporal and sequential data analysis*

| Direction      | GitHub Link                                                                                                                                                                                                                       | Description                                                     | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| -------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------- | ---------- | ------------ | ---------- | ------------- | --------- |
| TimeSeries LLM | [qingsongedu/Awesome-TimeSeries-SpatioTemporal-LM-LLM](https://github.com/qingsongedu/Awesome-TimeSeries-SpatioTemporal-LM-LLM) ![](https://img.shields.io/github/stars/qingsongedu/Awesome-TimeSeries-SpatioTemporal-LM-LLM.svg) | Resources for time series and spatiotemporal analysis with LLMs |            | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |

---

### 📑 LLM Survey
*Comprehensive surveys and overview papers on LLM research*

---

### 📊 LLM & Tables & Text2SQL
*Transforming natural language into SQL queries and understanding tabular data*

| Direction   | GitHub Link                                                                                                                                                  | Description                                  | Paper Link | Content Type    | Difficulty  | Update Status | Rec Score |
| ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------- | ---------- | --------------- | ----------- | ------------- | --------- |
| LLM Tabular | [johnnyhwu/Awesome-LLM-Tabular](https://github.com/johnnyhwu/Awesome-LLM-Tabular) ![](https://img.shields.io/github/stars/johnnyhwu/Awesome-LLM-Tabular.svg) | Resources for LLMs working with tabular data |            | 📄Papers        | ⭐⭐⭐Advanced | 🟢Active      | ★★★★★     |
| Text2SQL    | [eosphoros-ai/Awesome-Text2SQL](https://github.com/eosphoros-ai/Awesome-Text2SQL) ![](https://img.shields.io/github/stars/eosphoros-ai/Awesome-Text2SQL.svg) | Resources for text-to-SQL generation         |            | 📄Papers+💻Code | ⭐⭐⭐Advanced | 🟢Active      | ★★★★★     |

---

### 📄 LLM & Document Intelligence
*Document understanding, parsing, and analysis with LLMs*

| Direction              | GitHub Link                                                                                                                                                                                            | Description                                                  | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------ | ---------- | ------------ | ---------- | ------------- | --------- |
| Document Understanding | [tstanislawek/awesome-document-understanding](https://github.com/tstanislawek/awesome-document-understanding) ![](https://img.shields.io/github/stars/tstanislawek/awesome-document-understanding.svg) | Resources for document understanding and processing          |            | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Document Understanding | [harrytea/Awesome-Document-Understanding](https://github.com/harrytea/Awesome-Document-Understanding) ![](https://img.shields.io/github/stars/harrytea/Awesome-Document-Understanding.svg)             | Comprehensive collection of document understanding resources |            | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★★     |
| Chart Understanding    | [khuangaf/Awesome-Chart-Understanding](https://github.com/khuangaf/Awesome-Chart-Understanding) ![](https://img.shields.io/github/stars/khuangaf/Awesome-Chart-Understanding.svg)                      | Resources for understanding and analyzing charts             |            | 📄Papers | ⭐⭐⭐Advanced | 🟢Active | ★★★★☆     |

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### 🛠️ Agent Frameworks
*Frameworks and tools for building AI agents*

---

### 💬 Prompt Engineering
*Master the art of crafting effective prompts for LLMs*

| Direction          | GitHub Link                                                                                                                                                                       | Description                                  | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| ------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------- | ---------- | ------------ | ---------- | ------------- | --------- |
| ChatGPT Prompt     | [f/awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) ![](https://img.shields.io/github/stars/f/awesome-chatgpt-prompts.svg)                                  | Collection of effective ChatGPT prompts      |            | 📚Resources | ⭐Beginner | 🟢Active | ★★★★★     |
| Gemini Image Prompts | [JimmyLv/awesome-nano-banana](https://github.com/JimmyLv/awesome-nano-banana) ![](https://img.shields.io/github/stars/JimmyLv/awesome-nano-banana.svg) | 97 cases: Gemini-2.5-Flash-Image vs GPT-4o with prompts |            | 📚Examples | ⭐⭐Intermediate | 🟢Active | ★★★★★     |
| GPT-4o Image Prompts | [jamez-bondos/awesome-gpt4o-images](https://github.com/jamez-bondos/awesome-gpt4o-images) ![](https://img.shields.io/github/stars/jamez-bondos/awesome-gpt4o-images.svg) | 100 cases: GPT-4o vs gpt-image-1 with prompts |            | 📚Examples | ⭐⭐Intermediate | 🟢Active | ★★★★★     |
| Prompt Engineering | [NirDiamant/Prompt_Engineering](https://github.com/NirDiamant/Prompt_Engineering) ![](https://img.shields.io/github/stars/NirDiamant/Prompt_Engineering.svg)                      | Resources for prompt engineering techniques  |            | 📚Tutorials | ⭐⭐Intermediate | 🟢Active | ★★★★★     |
| AI System Prompts  | [dontriskit/awesome-ai-system-prompts](https://github.com/dontriskit/awesome-ai-system-prompts) ![](https://img.shields.io/github/stars/dontriskit/awesome-ai-system-prompts.svg) | System prompts for major LLM/Agent platforms |            | 📚Resources | ⭐⭐Intermediate | 🟢Active | ★★★★★     |

---

### 📚 arXiv & Paper Tools
*Stay updated with the latest research papers*

---

### 🔬 AI4Science & Scientific Discovery
*Accelerating scientific research with large language models*

| Direction | GitHub Link | Description | Paper Link | Content Type | Difficulty | Update Status | Rec Score |
| --------- | ----------- | ----------- | ---------- | ------------ | ---------- | ------------- | --------- |
| LLM Scientific Discovery | [HKUST-KnowComp/Awesome-LLM-Scientific-Discovery](https://github.com/HKUST-KnowComp/Awesome-LLM-Scientific-Discovery) ![](https://img.shields.io/github/stars/HKUST-KnowComp/Awesome-LLM-Scientific-Discovery.svg) | LLMs in scientific research: papers, tools, resources |  | 📄Papers+🛠️Tools | ⭐⭐⭐Advanced | 🟢Active | ★★★★★ |

---

### 🔌 MCP & Servers & Chinese Resources
*Model Context Protocol and server implementations*

---

### 📊 LLM Engineering & Monitoring
*Production-ready LLM deployment and monitoring solutions*

---

## 🤝 Contribution Guidelines

We warmly welcome contributions from the community! Your input helps keep this meta-collection comprehensive and up-to-date.

### How to Contribute

1. **Fork** this repository
2. **Add** your repository link to the appropriate category
3. **Follow** the format: `| Direction | [Owner/Repo-Name](URL) ![](https://raw.githubusercontent.com/adongwanai/Awesome-Awesome-LLMs/main/badge) | Description | Paper Link | Rating |`
4. **Submit** a Pull Request with a clear description

### Contribution Standards

Before submitting, please ensure:

✅ **Quality**: The repository is actively maintained (updated within the last 6 months)  
✅ **Relevance**: Directly related to LLM research or applications  
✅ **Value**: Contains substantial content (not just a few links)  
✅ **Description**: Includes a clear, concise description of what it offers  
✅ **Unique**: Not already listed in this collection

### Rating Guidelines

We use a 5-star rating system based on:
- **★★★★★** (5 stars): Comprehensive, frequently updated, highly cited
- **★★★★☆** (4 stars): High quality, good coverage, regularly maintained
- **★★★☆☆** (3 stars): Useful but limited scope or less frequent updates
- **★★☆☆☆** (2 stars): Niche topic or early stage
- **★☆☆☆☆** (1 star): Minimal content or rarely updated

### What We're Looking For

🔍 **Priority Areas:**
- Emerging LLM techniques (e.g., sparse attention, efficient training)
- Domain-specific applications (e.g., healthcare, legal, education)
- Multilingual resources (especially underrepresented languages)
- Practical implementation guides and tutorials
- Evaluation frameworks and datasets

### Questions or Suggestions?

- Open an **Issue** for discussions or questions
- Check existing **Pull Requests** to avoid duplicates
- Follow our **Code of Conduct** (be respectful and constructive)

---

## 🙏 Acknowledgments

This project stands on the shoulders of giants. We are deeply grateful to:

### Core Inspiration
- The **[Awesome](https://github.com/sindresorhus/awesome)** movement for pioneering community-curated knowledge
- All maintainers of the 200+ repositories featured in this collection
- The global LLM research community for their tireless work

### Special Thanks
- **Original Contributors** who started this meta-collection journey
- **Community Members** who submit issues, PRs, and suggestions
- **Researchers & Developers** worldwide who make their work openly accessible

### Built With Love By
- 🌍 **The Open Source Community**
- 🧠 **LLM Researchers & Practitioners**
- 💻 **Developers Building the AI Future**

> *"If I have seen further, it is by standing on the shoulders of giants."* - Isaac Newton

---

### 📈 Project Stats & Growth

![GitHub Created At](https://img.shields.io/github/created-at/adongwanai/Awesome-Awesome-LLMs)
![GitHub commit activity](https://img.shields.io/github/commit-activity/m/adongwanai/Awesome-Awesome-LLMs)
![GitHub contributors](https://img.shields.io/github/contributors/adongwanai/Awesome-Awesome-LLMs)

**Join us in organizing the world's LLM knowledge!**

</div>

---

## 📜 License

[![CC BY 4.0](https://licensebuttons.net/l/by/4.0/88x31.png)](https://creativecommons.org/licenses/by/4.0/)

This repository is licensed under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).

**You are free to:**
- ✅ **Share** — copy and redistribute the material
- ✅ **Adapt** — remix, transform, and build upon the material
- ✅ **Commercial use** — use for any purpose

**Under the following terms:**
- 📝 **Attribution** — give appropriate credit and link to the license

</div>

---

## 🌟 Star History

[![Star History Chart](https://api.star-history.com/svg?repos=adongwanai/Awesome-Awesome-LLMs&type=Date)](https://star-history.com/#adongwanai/Awesome-Awesome-LLMs&Date)

---

### 💬 Connect & Stay Updated

**Found this helpful?** Give us a ⭐ on [GitHub](https://github.com/adongwanai/Awesome-Awesome-LLMs)!

**Have suggestions?** Open an [Issue](https://github.com/adongwanai/Awesome-Awesome-LLMs/issues) or submit a [Pull Request](https://github.com/adongwanai/Awesome-Awesome-LLMs/pulls)!

**Share with others:** Help the community discover this resource!

---

### 🚀 Quick Links

[🏠 Home](https://github.com/adongwanai/Awesome-Awesome-LLMs) • 
[📖 Documentation](#table-of-contents) • 
[🤝 Contributing](#contribution-guidelines) • 
[📜 License](#license) • 
[⭐ Star](https://github.com/adongwanai/Awesome-Awesome-LLMs)

---

<sub>Made with ❤️ by the LLM community | Last updated: 2025</sub>

<sub>**Awesome-Awesome-LLMs** - Your gateway to the world of Large Language Models</sub>

</div>

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