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Awesome-Colorful-LLM

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Recent advancements propelled by large language models (LLMs), encompassing an array of domains including Vision, Audio, Agent, Robotics, Fundamental Sciences such as Mathematics, and Ominous.

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<h1 align="center" class="ui-bar-a"> <img alt="awesome-colorful-ai" src="assets/logo.png" width="60"> Colorful Multimodal Research</h1>

Welcome to our meticulously assembled anthology of vibrant multimodal research, encompassing an array of domains including **Vision**, **Audio**, **Agent**, **Robotics**, **Fundamental Sciences**, and **Ominous** including anything you want. Our collection primarily focuses on the advancements propelled by **large language models (LLMs)**, complemented by an assortment of related collections.

## 📚 Table of Contents

- [📚 Table of Contents](#-table-of-contents)
- [👀 Vision](#-vision)
  - [🖼 Image](#-image)
  - [📺 Video](#-video)
  - [📷 3D](#-3d)
  - [📰 Document](#-document)
  - [👁️ Vision Encoder](#️-vision-encoder)
- [👂 Audio](#-audio)
- [🔧 Agent](#-agent)
- [🤖 Robotic](#-robotic)
- [🔬 Science](#-science)
  - [♾️ AI for Math](#️-ai-for-math)
  - [📝 AI for Scientific Research](#-ai-for-scientific-research)
- [🌏 Ominous](#-ominous)
- [🙌 Contributing](#-contributing)

## 👀 Vision

### 🖼 Image

Collection of works about Image + LLMs, Diffusion, see [Image](Vision/Image.md) for details

> - Image Understanding
>   - Reading List
>   - Datasets & Benchmarks
> - Image Generation
>   - Reading List
> - Open-source Projects

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Tutorials

- [CVPR2024 Tutorial] [Recent Advances in Vision Foundation Models](https://vlp-tutorial.github.io/)
  - Large Multimodal Models: Towards Building General-Purpose Multimodal Assistant, Chunyuan Li
  - Methods, Analysis & Insights from Multimodal LLM Pre-training, Zhe Gan
  - LMMs with Fine-Grained Grounding Capabilities, Haotian Zhang
  - A Close Look at Vision in Large Multimodal Models, Jianwei Yang
  - Multimodal Agents, Linjie Li
  - Recent Advances in Image Generative Foundation Models, Zhengyuan Yang
  - Video and 3D Generation, Kevin Lin
- [CVPR2023 Tutorial] [Recent Advances in Vision Foundation Models](https://vlp-tutorial.github.io/2023/index.html)
  - Opening Remarks & Visual and Vision-Language Pre-training, Zhe Gan
  - From Representation to Interface: The Evolution of Foundation for Vision Understanding, Jianwei Yang
  - Alignments in Text-to-Image Generation, Zhengyuan Yang
  - Large Multimodal Models, Chunyuan Li
  - Multimodal Agents: Chaining Multimodal Experts with LLMs, Linjie Li
- [CVPR2022 Tutorial] [Recent Advances in Vision-and-Language Pre-training](https://vlp-tutorial.github.io/2022/index.html)
- [CVPR2021 Tutorial] [From VQA to VLN: Recent Advances in Vision-and-Language Research](https://vqa2vln-tutorial.github.io/)
- [CVPR2020 Tutorial] [Recent Advances in Vision-and-Language Research](https://rohit497.github.io/Recent-Advances-in-Vision-and-Language-Research/)

### 📺 Video

Collection of works about Video-Language Pretraining, Video + LLMs, see [Video](Vision/Video.md) for details

> - Video Understanding
>   - Reading List
>   - Pretraining Tasks
>   - Datasets
>     - Pretraining Corpora
>     - Video Instructions
>   - Benchmarks
>     - Common Downstream Tasks
>     - Advanced Downstream Tasks
>       - Task-Specific Benchmarks
>       - Multifaceted Benchmarks
>   - Metrics
>   - Projects & Tools
> - Video Generation
>   - Reading List
>   - Metrics
>   - Projects

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### 📷 3D

Collection of works about 3D+LLM, see [3D](Vision/3D.md) for details

> - Reading List

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### 📰 Document

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### 👁️ Vision Encoder

Collection of existing popular vision encoder, see [Vision Encoder](Vision/VisionEncoder.md) for details

> - Image Encoder
> - Video Encoder
> - Audio Encoder

## 👂 Audio

Collection of works about audio+LLM, see [Audio](Audio/Audio.md) for details

> - Reading List

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## 🔧 Agent

Collection of works about agent learning, see [Agent](Agents/Agent.md) for details

> - Reading List
> - Datasets & Benchmarks
> - Projects
> - Applications

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- [LLM-powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/), Lil'Log, Overview: panning, memory, tool use
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## 🤖 Robotic

Collection of works about robotics+LLM, see [Robotic](Robotic/Robotic.md) for details

> - Reading List

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- [Awesome-Robotics-Foundation-Models](https://github.com/robotics-survey/Awesome-Robotics-Foundation-Models) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/robotics-survey/Awesome-Robotics-Foundation-Models?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/robotics-survey/Awesome-Robotics-Foundation-Models.svg?style=social&label=Star), This is the partner repository for the survey paper "Foundation Models in Robotics: Applications, Challenges, and the Future". The authors hope this repository can act as a quick reference for roboticists who wish to read the relevant papers and implement the associated methods.
- [Awesome-LLM-Robotics](https://github.com/GT-RIPL/Awesome-LLM-Robotics) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/GT-RIPL/Awesome-LLM-Robotics?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/GT-RIPL/Awesome-LLM-Robotics.svg?style=social&label=Star), This repo contains a curative list of papers using Large Language/Multi-Modal Models for Robotics/RL
- [Simulately](https://github.com/geng-haoran/Simulately) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/geng-haoran/Simulately?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/geng-haoran/Simulately.svg?style=social&label=Star), a website where we gather useful information of physics simulator for cutting-edge robot learning research. It is still under active development, so stay tuned!
- [Awesome-Temporal-Action-Detection-Temporal-Action-Proposal-Generation](https://github.com/zhenyingfang/Awesome-Temporal-Action-Detection-Temporal-Action-Proposal-Generation) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/zhenyingfang/Awesome-Temporal-Action-Detection-Temporal-Action-Proposal-Generation?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/zhenyingfang/Awesome-Temporal-Action-Detection-Temporal-Action-Proposal-Generation.svg?style=social&label=Star), Temporal Action Detection & Weakly Supervised & Semi Supervised Temporal Action Detection & Temporal Action Proposal Generation & Open-Vocabulary Temporal Action Detection.
- [Awesome-TimeSeries-SpatioTemporal-LM-LLM](https://github.com/qingsongedu/Awesome-TimeSeries-SpatioTemporal-LM-LLM) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/qingsongedu/Awesome-TimeSeries-SpatioTemporal-LM-LLM?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/qingsongedu/Awesome-TimeSeries-SpatioTemporal-LM-LLM.svg?style=social&label=Star), A professionally curated list of **Large (Language) Models and Foundation Models (LLM, LM, FM) for Temporal Data (Time Series, Spatio-temporal, and Event Data)** with awesome resources (paper, code, data, etc.), which aims to comprehensively and systematically summarize the recent advances to the best of our knowledge.
- [PromptCraft-Robotics](https://github.com/microsoft/PromptCraft-Robotics) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/microsoft/PromptCraft-Robotics?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/microsoft/PromptCraft-Robotics.svg?style=social&label=Star), The PromptCraft-Robotics repository serves as a community for people to test and share interesting prompting examples for large language models (LLMs) within the robotics domain
- [Awesome-Robotics](https://github.com/ahundt/awesome-robotics) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/ahundt/awesome-robotics?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/ahundt/awesome-robotics.svg?style=social&label=Star), A curated list of awesome links and software libraries that are useful for robots

Related Collections (embodied)

- [Embodied_AI_Paper_List](https://github.com/HCPLab-SYSU/Embodied_AI_Paper_List) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/HCPLab-SYSU/Embodied_AI_Paper_List?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/HCPLab-SYSU/Embodied_AI_Paper_List.svg?style=social&label=Star), Awesome Paper list for Embodied AI and its related projects and applications
- [Awesome-Embodied-AI](https://github.com/haoranD/Awesome-Embodied-AI) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/haoranD/Awesome-Embodied-AI?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/haoranD/Awesome-Embodied-AI.svg?style=social&label=Star), A curated list of awesome papers on Embodied AI and related research/industry-driven resources
- [awesome-embodied-vision](https://github.com/ChanganVR/awesome-embodied-vision) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/ChanganVR/awesome-embodied-vision?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/ChanganVR/awesome-embodied-vision.svg?style=social&label=Star), Reading list for research topics in embodied vision

Related Collections (autonomous driving)

- [Awesome-LLM4AD](https://github.com/Thinklab-SJTU/Awesome-LLM4AD) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/Thinklab-SJTU/Awesome-LLM4AD?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/ChangThinklab-SJTUanVR/Awesome-LLM4AD.svg?style=social&label=Star), A curated list of awesome LLM for Autonomous Driving resources (continually updated)

## 🔬 Science

### ♾️ AI for Math

Collection of works about Mathematics + LLMs, see [AI4Math](AI4Science/AI4Math.md) for details

> - Reading List

Related Collections

- [Awesome-Scientific-Language-Models](https://github.com/yuzhimanhua/Awesome-Scientific-Language-Models) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/yuzhimanhua/Awesome-Scientific-Language-Models?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/yuzhimanhua/Awesome-Scientific-Language-Models.svg?style=social&label=Star), A curated list of pre-trained language models in scientific domains (e.g., mathematics, physics, chemistry, biology, medicine, materials science, and geoscience), covering different model sizes (from <100M to 70B parameters) and modalities (e.g., language, vision, molecule, protein, graph, and table)

### 📝 AI for Scientific Research

- [CAJAL](https://github.com/Agnuxo1/CAJAL) ![GitHub last commit](https://img.shields.io/github/last-commit/Agnuxo1/CAJAL?style=flat)![GitHub stars](https://img.shields.io/github/stars/Agnuxo1/CAJAL.svg?style=social&label=Star), A fine-tuned open-source LLM (Qwen3.6 base) specialized for generating publication-ready scientific papers. Runs 100% locally with 4B–9B parameters, ranked #3 on scientific paper benchmarks, surpassing most SOTA cloud models including Claude Sonnet 4.6 competitors.

## 🌏 Ominous

Collection of works about LLM + ominous modality, see [Omni](Omni/omni.md) for details

Related Collections

> - Reading List
> - Dataset
> - Benchmark

- [Awesome-Unified-Multimodal-Models](https://github.com/showlab/Awesome-Unified-Multimodal-Models) ![GitHub last commit (by committer)](https://img.shields.io/github/last-commit/showlab/Awesome-Unified-Multimodal-Models?style=flat)![Dynamic JSON Badge](https://img.shields.io/github/stars/showlab/Awesome-Unified-Multimodal-Models.svg?style=social&label=Star), This is a repository for organizing papers, codes and other resources related to unified multimodal models.

## 🙌 Contributing

Please freely create a [pull request](https://github.com/patrick-tssn/Awesome-Colorful-LLM/pulls) or drop me an email: [flagwyx@gmail.com](flagwyx@gmail.com)

Awesome-Colorful-LLM

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