{"data":{"slug":"activevisionlab-awesome-llm-3d","name":"Awesome-LLM-3D","tagline":"Curated list of Multi-modal Large Language Model resources in 3D world","github_url":"https://github.com/ActiveVisionLab/Awesome-LLM-3D","owner":"ActiveVisionLab","repo":"Awesome-LLM-3D","owner_avatar_url":"https://avatars.githubusercontent.com/u/21082947?v=4","primary_language":null,"stars":2269,"forks":145,"topics":[],"archived":false,"github_pushed_at":"2026-04-16T16:28:04+00:00","maintenance_label":"Slowing","stars_delta_30d":14,"url":"https://www.graphcanon.com/tools/activevisionlab-awesome-llm-3d","markdown_url":"https://www.graphcanon.com/tools/activevisionlab-awesome-llm-3d.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/activevisionlab-awesome-llm-3d","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=activevisionlab-awesome-llm-3d","description":"Awesome-LLM-3D: a curated list of Multi-modal Large Language Model in 3D world  Resources","homepage_url":null,"license":"MIT","open_issues":8,"watchers":58,"ai_summary":"Awesome-LLM-3D is a curated list of papers and resources related to 3D tasks empowered by Large Language Models (LLMs), including 3D understanding, reasoning, generation, and embodied agents. It also includes other Foundation Models like CLIP and SAM.","readme_excerpt":"# Awesome-LLM-3D     <a href=\"\" target='_blank'><img src=\"https://visitor-badge.laobi.icu/badge?page_id=activevisionlab.llm3d&left_color=gray&right_color=blue\"> </a> \n\n<div align=\"center\">\n    <img src=\"assets/Figure1_v8_25.6.9.png\" width=\"100%\">\n</div>\n\n\n\n## 🏠 About\nHere is a curated list of papers about 3D-Related Tasks empowered by Large Language Models (LLMs). \nIt contains various tasks including 3D understanding, reasoning, generation, and embodied agents. Also, we include other Foundation Models (CLIP, SAM) for the whole picture of this area.\n\nThis is an active repository, you can watch for following the latest advances. If you find it useful, please kindly star ⭐ this repo and [cite](#citation) the paper.\n\n## 🔥 News\n- [2026-03-20] Our benchmark paper **Real-3DQA** is now available at ICLR 2026! Following our survey paper, we now release the benchmark paper on genuine 3D spatial understanding. [Project Page](https://real-3dqa.github.io/)\n- [2025-10-21] 📢 We have released the **second version** of our survey, updated to include literature up to **July 2025**:  \n👉 [*When LLMs Step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models*](https://arxiv.org/pdf/2405.10255v2)\n- [2024-05-16] Check out the first survey paper in the 3D-LLM domain: [When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models](https://arxiv.org/pdf/2405.10255) \n- [2024-01-06] [Runsen Xu](https://runsenxu.com/) added chronological information and [Xianzheng Ma](https://xianzhengma.github.io/) reorganized it in Z-A order for better following the latest advances.\n- [2023-12-16] [Xianzheng Ma](https://xianzhengma.github.io/) and [Yash Bhalgat](https://yashbhalgat.github.io/) curated this list and published the first version;\n\n## Table of Contents\n\n- [Awesome-LLM-3D](#awesome-llm-3D)\n  - [3D Unified Understanding and Generation (LLM)](#3d-unified-understanding-and-generation-via-llm)\n  - [3D Understanding (LLM)](#3d-understanding-via-llm)\n  - [3D Understanding (other Foundation Models)](#3d-understanding-via-other-foundation-models)\n  - [3D Reasoning](#3d-reasoning)\n  - [3D Generation](#3d-generation)\n  - [3D Embodied Agent](#3d-embodied-agent)\n  - [3D Benchmarks](#3d-benchmarks)\n  - [Contributing](#contributing)\n\n\n## 3D Unified Understanding and Generation via LLM\n\n|  Date |       Keywords       |    Institute (first)   | Paper                                                                                                                                                                               | Publication | Others |\n| :-----: | :------------------: | :--------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :---------: | :---------:\n| 2025-11-07 | Omni-View | PKU | [Omni-View: Unlocking How Generation Facilitates Understanding in Unified 3D Model based on Multiview images](https://arxiv.org/abs/2511.07222) | ICLR 2026 | [github](https://github.com/AIDC-AI/Omni-View) |\n| 2025-08-16 | UniUGG | FDU | [UniUGG: Unified 3D Understanding and Generation via Geometric-Semantic Encoding](https://arxiv.org/abs/2508.11952) | ICLR 2026 | [github](https://github.com/fudan-zvg/UniUGG) |\n\n## 3D Understanding via LLM\n\n|  Date |       Keywords       |    Institute (first)   | Paper                                                                                                                                                                               | Publication | Others |\n| :-----: | :------------------: | :--------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :---------: | :---------:\n| 2026-03-07 | 3D-RFT | BIGAI | [3D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene Unde","github_created_at":"2023-12-15T06:02:44+00:00","created_at":"2026-07-11T10:33:06.235013+00:00","updated_at":"2026-10-12T06:00:12.463431+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"}],"tags":[{"slug":"3d-embodied-agent","name":"3d embodied agent"},{"slug":"3d-generation","name":"3d generation"},{"slug":"3d-reasoning","name":"3d reasoning"},{"slug":"3d-understanding","name":"3d understanding"},{"slug":"foundation-models","name":"foundation models"},{"slug":"large-language-models","name":"large-language-models"},{"slug":"multi-modal-models","name":"multi-modal models"},{"slug":"survey-papers","name":"survey papers"}],"trust":{"provenance":{"is_fork":false,"github_id":731892810,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-10-12T06:00:11.608Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":178,"last_release_at":null,"stars_delta_30d":14,"open_issues_delta_30d":1},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T10:33:07.407Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-10-12T06:00:12.116Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-10-12T06:00:12.116Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["The repository does not specify any programming language requirements, making it accessible to a wide range of users.","Users should have a basic understanding of 3D tasks and Large Language Models to effectively utilize the resources provided."]},"constraints":null,"when_to_use":["Use Awesome-LLM-3D when you need a comprehensive list of resources and papers focused on the intersection of 3D tasks and Large Language Models, including recent advancements like the Real-3DQA paper.","Utilize this repository if you are interested in the latest research on 3D understanding, reasoning, generation, and embodied agents, as it includes chronological updates and is actively maintained."],"when_not_to_use":["Avoid using Awesome-LLM-3D if you are looking for a repository that includes practical code implementations or tutorials, as it primarily focuses on curating research papers and resources.","Do not use this repository if you require real-time updates or interactive tools for 3D tasks, as it is a static list of papers and resources without interactive features."],"source":"enrich:decision_facts","observed_at":"2026-09-30T21:34:59.384Z"},"constraint_facets":null,"decision_summary":[{"label":"Requirements","value":"The repository does not specify any programming language requirements, making it accessible to a wide range of users.; Users should have a basic understanding of 3D tasks and Large Language Models to effectively utilize the resources provided."},{"label":"Adopt for","value":"Awesome-LLM-3D is a curated list of resources and papers related to 3D tasks empowered by Large Language Models (LLMs), including 3D understanding, reasoning, generation, and embodied agents. It also includes other types"},{"label":"License detail","value":"MIT License"}]}}