🤖 Awesome Embodied Robotics and Agent

This is a curated list of "Embodied robotics or agent with Vision-Language Models (VLMs) and Large Language Models (LLMs)" research which is maintained by haonan.

Watch this repository for the latest updates and feel free to raise pull requests if you find some interesting papers!

News🔥

[2026/09/10] 🎉 Our survey paper "A Survey on Efficient Vision-Language-Action Models" has been accepted by IEEE TPAMI!

[2026/05/11] 🎉 Add NavSpace: How Intelligent Agents Follow Spatial Intelligence Instructions (ICRA 2026), the first benchmark for evaluating spatial intelligence in embodied navigation, with open-sourced dataset, evaluation code, and baseline SNav. [arXiv] [Github]

[2025/10/30] 🎉 Our survey paper "A Survey on Efficient Vision-Language-Action Models" [arXiv] has been released!

[2025/04/23] Add π-0.5, a lightweight and modular framework designed to integrate perception, control, and learning directly within physical systems.

[2025/03/18] Add some popular vision-language action (VLA) models. 🦾

[2024/06/28] Created a new board about agent self-evolutionary research. 🤖

[2024/06/07] Add Mobile-Agent-v2, a mobile device operation assistant with effective navigation via multi-agent collaboration. 🚀

[2024/05/13] Add "Learning Interactive Real-World Simulators"——outstanding paper award in ICLR 2024 🥇.

[2024/04/24] Add "A Survey on Self-Evolution of Large Language Models", a systematic survey on self-evolution in LLMs! 💥

[2024/04/16] Add some CVPR 2024 papers.

[2024/04/15] Add MetaGPT, accepted for oral presentation (top 1.2%) at ICLR 2024, ranking #1 in the LLM-based Agent category. 🚀

[2024/03/13] Add CRADLE, an interesting paper exploring LLM-based agent in Red Dead Redemption II！🎮

Development of Embodied Robotics and Benchmarks

• Continuum-AI-Corp/OrcaReplay — record & replay AI coding-agent runs offline.

  

Figure 1. The Organization of Our Survey. We systematically categorize efficient VLAs into three core pillars: (1) Efficient Model Design, encompassing efficient architectures and model compression techniques, (2) Efficient Training, covering efficient pre-training and post-training strategies, and (3) Efficient Data Collection, including efficient data collection and augmentation methods. The framework also reviews VLA foundations, key applications, challenges, and future directions, establishing the groundwork for advancing scalable embodied intelligence.

Table of Contents 🍃

• Survey
• Vision-Language-Action Model
• Self-Evolving Agents
• Advanced Agent Applications
• LLMs with RL or World Model
• Planning and Manipulation or Pretraining
• Multi-Agent Learning and Coordination
• Vision and Language Navigation
• Detection
• 3D Grounding
• Interactive Embodied Learning
• Rearrangement
• Benchmark
• Simulator
• Others

Methods

Survey

• LLM Agents: A Survey [Preprints.org 2026.08] [Github]

Jungseob Lee

Korea University

• A Survey on Efficient Vision-Language-Action Models [arXiv 2025.10] [Github] [Project Page]

Zhaoshu Yu1, Bo Wang1, Pengpeng Zeng1, Haonan Zhang1, Ji Zhang1, Lianli Gao3, Jingkuan Song1, Nicu Sebe4, Heng Tao Shen1

1 Tongji University, 2 Southwest Jiaotong University, 3 University of Electronic Science and Technology of China, 4 University of Trento

• A Survey on Vision-Language-Action Models for Embodied AI [arXiv 2024.03]

The Chinese University of Hong Kong, Huawei Noah’s Ark Lab

• Large Multimodal Agents: A Survey [arXiv 2024.02] [Github]

Junlin Xie♣♡ Zhihong Chen♣♡ Ruifei Zhang♣♡ Xiang Wan♣ Guanbin Li♠

♡The Chinese University of Hong Kong, Shenzhen ♣Shenzhen Research Institute of Big Data, ♠Sun Yat-sen University

• A Survey on Self-Evolution of Large Language Models [arXiv 2024.01]

Key Lab of HCST (PKU), MOE; School of Computer Science, Peking University, Alibaba Group, Nanyang Technological University

• Agent AI: Surveying the Horizons of Multimodal Interaction [arXiv 2024.01]

Stanford University, Microsoft Research, Redmond, University of California, Los Angeles, University of Washington, Microsoft Gaming

• Igniting Language Intelligence: The Hitchhiker’s Guide From Chain-of-Thought Reasoning to Language Agents [arXiv 2023.11]

Shanghai Jiao Tong University, Amazon Web Services, Yale University

• The Rise and Potential of Large Language Model Based Agents: A Survey [arXiv 2023.09]

Fudan NLP Group, miHoYo Inc

• A Survey on LLM-based Autonomous Agents [arXiv 2023,08]

Gaoling School of Artificial Intelligence, Renmin University of China

Vision-Language-Action Model

• ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning [arXiv 2026] [Github][Project page]

AMAP CV Lab, Alibaba Group

• D2E: Scaling Vision-Action Pretraining on Desktop Data for Transfer to Embodied AI [ICLR 2026] [Github][Project page][HuggingFace🤗]

Stanford University, Seoul National University, MAUM.AI

• Robotic Control via Embodied Chain-of-Thought Reasoning [CoRL 2024] [Github][Project page][HuggingFace🤗]

Michał Zawalski∗1,2, William Chen∗1, Karl Pertsch1,3 Oier Mees1, Chelsea Finn3, Sergey Levine1

1UC Berkeley, 2University of Warsaw, 3Stanford University

• π0.5: a VLA with Open-World Generalization [arXiv 2025.04] [Project page]

Physical Intelligence

• π0: A Vision-Language-Action Flow Model for General Robot Control [arXiv 2024.10] [Project page]

Physical Intelligence

• Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models [arXiv 2025.02] [Project page]

Physical Intelligence

• OpenVLA: An Open-Source Vision-Language-Action Model [arXiv 2024.01] [Github][Project page][HuggingFace🤗]

Stanford University, UC Berkeley, Toyota Research Institute, Google Deepmind, Physical Intelligence, MIT

• FAST: Efficient Action Tokenization for Vision-Language-Action Models [arXiv 2025.01] [Project page][HuggingFace🤗]

Physical Intelligence

• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control [arXiv 2024.07] [Project Page]

Google Deepmind

• Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks [arXiv 2025.03] [Github] [Project Page] [HuggingFace🤗]

Zhejiang University; Institute of Software, Chinese Academy of Sciences; Alibaba Group

Self-Evolving Agents

• VLM Can Be a Good Assistant: Enhancing Embodied Visual Tracking with Self-Improving Vision-Language Models [IROS 2025] [Project page]

Kui Wu1, Shuhang Xu2, Hao Chen3, Churan Wang4, Zhoujun Li1, Yizhou Wang4, Fangwei Zhong2

1Beihang University, 2Beijing Normal University, 3City University of Macau, 4Peking University

• Hierarchical Instruction-aware Embodied Visual Tracking [arXiv 2025] [Project page]

Kui Wu1, Hao Chen2, Churan Wang3, Fakhri Karray4, Zhoujun Li1, Yizhou Wang3, Fangwei Zhong5

1Beihang University, 2City University of Macau, 3Peking University, 4Mohamed bin Zayed University of Artificial Intelligence, 5Beijing Normal University

• AdaTracker: Learning Adaptive In-Context Policy for Cross-Embodiment Active Visual Tracking [IEEE RA-L 2026]

Kui Wu1, Hao Chen2, Jinzhu Han3, Haijun Liu4, Churan Wang5, Yizhou Wang6, Zhoujun Li1, Si Liu1, Fangwei Zhong3

1Beihang University, 2City University of Macau, 3Beijing Normal University, 4Minzu University of China, 5Peking University Third Hospital, 6Peking University

• Meta-Control: Automatic Model-based Control System Synthesis for Heterogeneous Robot Skills [CoRL 2024] [Project page]

Tianhao Wei1*, Liqian Ma12*, Rui Chen1, Weiye Zhao1, Changliu Liu1

1Carnegie Mellon University 2Tsinghua University

• AGENTGYM: Evolving Large Language Model-based Agents across Diverse Environments [arXiv 2024.06] [Github] [Project page]

Fudan NLP Lab & Fudan Vision and Learning Lab

• Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models [arXiv 2024.06] [Github]

Fangzhi Xu♢♡, Qiushi Sun2, ♡, Kanzhi Cheng1, Jun Liu♢, Yu Qiao♡, Zhiyong Wu♡

♢Xi’an Jiaotong University, ♡Shanghai Artificial Intelligence Laboratory, 1The University of Hong Kong, 2Nanjing Univerisity

• Symbolic Learning Enables Self-Evolving Agents [arXiv 2024.06] [Github]

Wangchunshu Zhou, Yixin Ou, Shengwei Ding, Long Li, Jialong Wu, Tiannan Wang, Jiamin Chen, Shuai Wang, Xiaohua Xu, Ningyu Zhang, Huajun Chen, Yuchen Eleanor Jiang

AIWaves Inc. https://meta-control-paper.github.io/

Advanced Agent Applications

• Meta-Control: Automatic Model-based Control System Synthesis for Heterogeneous Robot Skills [CoRL 2024] [Project page]

Tianhao Wei1*, Liqian Ma12*, Rui Chen1, Weiye Zhao1, Changliu Liu1

*Equal Contribution 1Carnegie Mellon University 2Tsinghua University

• [Embodied-agents] [Github]

Seamlessly integrate state-of-the-art transformer models into robotics stacks.

• Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration [arXiv 2024] [Github]

Junyang Wang1, Haiyang Xu2, Haitao Jia1, Xi Zhang2, Ming Yan2, Weizhou Shen2, Ji Zhang2, Fei Huang2, Jitao Sang1

1Beijing Jiaotong University 2Alibaba Group

• Mobile-Agent: The Powerful Mobile Device Operation Assistant Family [ICLR 2024 Workshop LLM Agents] [Github]

Junyang Wang1, Haiyang Xu2, Jiabo Ye2, Ming Yan2, Weizhou Shen2, Ji Zhang2, Fei Huang2, Jitao Sang1

1Beijing Jiaotong University 2Alibaba Group

• [Machinascript-for-robots] [Github]

Build LLM-powered robots in your garage with MachinaScript For Robots!

• [ros2_medkit] [Github] [MCP Server]

LLM-powered robot diagnostics for ROS 2 — fault detection, root cause analysis, and self-healing via MCP.

• DiffAgent: Fast and Accurate Text-to-Image API Selection with Large Language Model [CVPR 2024] [Github]

Lirui Zhao1,2 Yue Yang2,4 Kaipeng Zhang2 Wenqi Shao2, Yuxin Zhang1, Yu Qiao2, Ping Luo2,3 Rongrong Ji1

1Xiamen University, 2OpenGVLab, Shanghai AI Laboratory 3The University of Hong Kong, 4Shanghai Jiao Tong University

• MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework [ICLR 2024 (oral)]

DeepWisdom, AI Initiative, King Abdullah University of Science and Technology, Xiamen University, The Chinese University of Hong Kong, Shenzhen, Nanjing University, University of Pennsylvania, University of California, Berkeley, The Swiss AI Lab IDSIA/USI/SUPSI

• AppAgent: Multimodal Agents as Smartphone Users [Project page] [Github]

Chi Zhang∗ ZhaoYang∗ JiaxuanLiu∗ YuchengHan XinChen Zebiao Huang BinFu GangYu†

Tencent

LLMs with RL or World Model

• Spatial-Interactor: Learning Spatial Reasoning through Interaction with the Observable Physical World [arXiv 2026.09] [Project Page] [Github] [HuggingFace🤗]

Kaixiang Yao1*, Xu Wang1*, Miao Pan1, Hu Xiyue1, Weishi Wang2, Daniel Dahlmeier2, Jintao Chen1, Yongliang Shen1, Xuhong Zhang1, Wenqi Zhang1

*Equal Contribution 1Zhejiang University 2SAP

• VAGEN: Reinforcing World Model Reasoning for Multi-Turn VLM Agents [NeurIPS 2025] [Project Page] [Github]

Kangrui Wang, Pingyue Zhang, Zihan Wang, Yaning Gao, Linjie Li, Qineng Wang, Hanyang Chen, Chi Wan, Yiping Lu, Zhengyuan Yang, Lijuan Wang, Ranjay Krishna, Jiajun Wu, Li Fei-Fei, Yejin Choi, Manling Li

• KALM: Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts [NeurIPS 2024] [Project Page]

Jing-Cheng Pang, Si-Hang Yang, Kaiyuan Li, Jiaji Zhang, Xiong-Hui Chen, Nan Tang, Yang Yu

1Nanjing University, 2Polixir.ai

• Learning Interactive Real-World Simulators [ICLR 2024 (Outstanding Papers)] [Project Page]

Sherry Yang1,2, Yilun Du3, Kamyar Ghasemipour2, Jonathan Tompson2, Leslie Kaelbling3, Dale Schuurmans2, Pieter Abbeel1

1UC Berkeley, 2Google DeepMind, 3MIT

• Robust agents learn causal world models [ICLR 2024]

Jonathan Richens*, TomEveritt

Google DeepMind

• Embodied Multi-Modal Agent trained by an LLM from a Parallel TextWorld [CVPR 2024] [Github]

Yijun Yang154, Tianyi Zhou2, Kanxue Li3, Dapeng Tao3, Lvsong Li4, Li Shen4, Xiaodong He4, Jing Jiang5, Yuhui Shi1

1Southern University of Science and Technology, 2University of Maryland, College Park, 3Yunnan University, 4JD Explore Academy, 5University of Technology Sydney

• Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning [NeurIPS 2023] [Project Page][Github]

Lin_Guan1, Karthik Valmeekam1, Sarath Sreedharan2, Subbarao Kambhampati1

1School of Computing & AI Arizona State University Tempe, AZ, 2Department of Computer Science Colorado State University Fort Collins, CO

• Eureka: Human-Level Reward Design via Coding Large Language Models [NeurIPS 2023 Workshop ALOE Spotlight] [Project page] [Github]

Jason Ma1,2, William Liang2, Guanzhi Wang1,3, De-An Huang1, Osbert Bastani2, Dinesh Jayaraman2, Yuke Zhu1,4, Linxi "Jim" Fan1, Anima Anandkumar1,3

1NVIDIA; 2UPenn; 3Caltech; 4UT Austin

• RLAdapter: Bridging Large Language Models to Reinforcement Learning in Open Worlds [arXiv 2023]

• Can Language Agents Be Alternatives to PPO? A Preliminary Empirical Study on OpenAI Gym [arXiv 2023]

• RoboGPT: An intelligent agent of making embodied long-term decisions for daily instruction tasks [arXiv 2023]

• Aligning Agents like Large Language Models [arXiv 2023]

• AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents [ICLR 2024 spotlight]

• STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models [arXiv 2023]

• Text2Reward: Dense Reward Generation with Language Models for Reinforcement Learning [ICLR 2024 spotlight]

• Leveraging Large Language Models for Optimised Coordination in Textual Multi-Agent Reinforcement Learning [arXiv 2023]

• Online Continual Learning for Interactive Instruction Following Agents [ICLR 2024]

• ADAPTER-RL: Adaptation of Any Agent using Reinforcement Learning [arXiv 2023]

• Language Reward Modulation for Pretraining Reinforcement Learning [arXiv 2023]

• Informing Reinforcement Learning Agents by Grounding Natural Language to Markov Decision Processes [arXiv 2023]

• Learning to Model the World with Language [arXiv 2023]

• MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning [ICLR 2024]

• Language Reward Modulation for Pretraining Reinforcement Learning [arXiv 2023] [Github]

Ademi Adeniji, Amber Xie, Carmelo Sferrazza, Younggyo Seo, Stephen James, Pieter Abbeel

1UC Berkeley

• Guiding Pretraining in Reinforcement Learning with Large Language Models [ICML 2023]

Yuqing Du1*, Olivia Watkins1*, Zihan Wang2, Cedric Colas ´3,4, Trevor Darrell1, Pieter Abbeel1, Abhishek Gupta2, Jacob Andreas3

1Department of Electrical Engineering and Computer Science, University of California, Berkeley, USA 2University of Washington, Seattle 3Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory 4 Inria, Flowers Laboratory.

Planning and Manipulation or Pretraining

• Planning with the Views via Scene Self-Exploration [arXiv 2026.05] [Project Page] [Github]

Kangrui Wang, Linjie Li, Zhengyuan Yang, Shiqi Chen, Zihan Wang, Li Fei-Fei, Jiajun Wu, Leonidas Guibas, Lijuan Wang, Manling Li

• RoboClaw: An Agentic Framework for Scalable Long-Horizon Robotic Tasks [arXiv 2026.03] [Project Page] [Github]

Ruiying Li*, Yunlang Zhou*, YuYao Zhu, Kylin Chen, Jingyuan Wang, Sukai Wang, Kongtao Hu, Minhui Yu, Bowen Jiang, Zhan Su, Jiayao Ma, Xin He, Yongjian Shen, Yang Yang, Guanghui Ren, Maoqing Yao, Wenhao Wang†, Yao Mu†

• RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics [Arxiv 2025] [Project Page] [Code]

Enshen Zhou1,2,, Jingkun An1,, Cheng Chi2,*

1Beihang University, 2Beijing Academy of Artificial Intelligence

• RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics [CVPR 2025 (Oral)] [Project Page] [Code]

Chan Hee Song1, Valts Blukis2, Jonathan Tremblay2, Stephen Tyree2, Yu Su1, Stan Birchfield2

1The Ohio State University, 2NVIDIA

• Multi-Modal Grounded Planning and Efficient Replanning For Learning Embodied Agents with A Few Examples [AAAI 2025] [Project page]

Taewoong Kim, Byeonghwi Kim, Jonghyun Choi†

Seoul National University

• Pre-emptive Action Revision by Environmental Feedback for Embodied Instruction Following Agents [CoRL 2024] [Project page]

Jinyeon Kim1,2,, Cheolhong Min1,, Byeonghwi Kim1, Jonghyun Choi1

1Seoul National University 2Yonsei University

• Meta-Control: Automatic Model-based Control System Synthesis for Heterogeneous Robot Skills [CoRL 2024] [Project page]

Tianhao Wei1*, Liqian Ma12*, Rui Chen1, Weiye Zhao1, Changliu Liu1 *Equal Contribution 1Carnegie Mellon University 2Tsinghua University

• Voyager: An Open-Ended Embodied Agent with Large Language Models [NeurIPS 2023 Workshop ALOE Spotlight] [Project page] [Github]

Guanzhi Wang1,2, Yuqi Xie3, Yunfan Jiang4, Ajay Mandlekar1, Chaowei Xiao1,5, Yuke Zhu1,3, Linxi Fan1, Anima Anandkumar1,2 1NVIDIA, 2Caltech, 3UT Austin, 4Stanford, 5UW Madison

• Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization [ACL 2024][Github]

Wenqi Zhang, Ke Tang, Hai Wu, Mengna Wang, Yongliang Shen, Guiyang Hou, Zeqi Tan, Peng Li, Yueting Zhuang, Weiming Lu

• Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives [ACL 2024]

Wenqi Zhang, Yongliang Shen, Linjuan Wu, Qiuying Peng, Jun Wang, Yueting Zhuang, Weiming Lu

• MineDreamer: Learning to Follow Instructions via Chain-of-Imagination for Simulated-World Control [arXiv 2024] [Project Page]

  Enshen Zhou1,2 Yiran Qin1,3 Zhenfei Yin1,4 Yuzhou Huang3 Ruimao Zhang3 Lu Sheng2 Yu Qiao1 Jing Shao1

  1Shanghai Artificial Intelligence Laboratory, 2The Chinese University of Hong Kong, Shenzhen, 3Beihang University, 4The University of Sydney

• MP5: A Multi-modal Open-ended Embodied System in Minecraft via Active Perception [CVPR 2024] [Project Page]

  Yiran Qin1,2 Enshen Zhou1,3 Qichang Liu1,4 Zhenfei Yin1,5 Lu Sheng3 Ruimao Zhang2 Yu Qiao1 Jing Shao1

  1Shanghai Artificial Intelligence Laboratory, 2The Chinese University of Hong Kong, Shenzhen, 3Beihang University, 4Tsinghua University, 5The University of Sydney

• Code-as-Monitor: Constraint-aware Visual Programming for Reactive and Proactive Robotic Failure Detection [CVPR 2025] [Project Page]

Enshen Zhou1* Qi Su2* Cheng Chi3*; Zhizheng Zhang4 Zhongyuan Wang3 Tiejun Huang2,3 Lu Sheng1; He Wang2,3,4;

1Beihang University, 2Peking University, 3Beijing Academy of Artificial Intelligence, 4GalBot

• RILA: Reflective and Imaginative Language Agent for Zero-Shot Semantic Audio-Visual Navigation [CVPR 2024]

Zeyuan Yang1, LIU JIAGENG, Peihao Chen2, Anoop Cherian3, Tim Marks, Jonathan Le Roux4, Chuang Gan5 1Tsinghua University, 2South China University of Technology, 3Mitsubishi Electric Research Labs (MERL), 4Mitsubishi Electric Research Labs, 5MIT-IBM Watson AI Lab

• Towards General Computer Control: A Multimodal Agent for Red Dead Redemption II as a Case Study [arXiv 2024] [Project Page] [Code]

Weihao Tan2, Ziluo Ding1, Wentao Zhang2, Boyu Li1, Bohan Zhou3, Junpeng Yue3, Haochong Xia2, Jiechuan Jiang3, Longtao Zheng2, Xinrun Xu1, Yifei Bi1, Pengjie Gu2,

1Beijing Academy of Artificial Intelligence (BAAI), China; 2Nanyang Technological University, Singapore; 3School of Computer Science, Peking University, China

• See and Think: Embodied Agent in Virtual Environment [arXiv 2023]

Zhonghan Zhao1*, Wenhao Chai2*, Xuan Wang1*, Li Boyi1, Shengyu Hao1, Shidong Cao1, Tian Ye3, Jenq-Neng Hwang2, Gaoang Wang1

1Zhejiang University 1University of Washington 1Hong Kong University of Science and Technology (GZ)

• Agent Instructs Large Language Models to be General Zero-Shot Reasoners [arXiv 2023]

Nicholas Crispino1, Kyle Montgomery1, Fankun Zeng1, Dawn Song2, Chenguang Wang1

1Washington University in St. Louis, 2UC Berkeley

• JARVIS-1: Open-world Multi-task Agents with Memory-Augmented Multimodal Language Models [NeurIPS 2023] [Project Page]

  Zihao Wang1,2 Shaofei Cai1,2 Anji Liu3 Yonggang Jin4 Jinbing Hou4 Bowei Zhang5 Haowei Lin1,2 Zhaofeng He4 Zilong Zheng6 Yaodong Yang1 Xiaojian Ma6† Yitao Liang1†

  1Institute for Artificial Intelligence, Peking University, 2School of Intelligence Science and Technology, Peking University, 3Computer Science Department, University of California, Los Angeles, 4Beijing University of Posts and Telecommunications, 5School of Electronics Engineering and Computer Science, Peking University, 6Beijing Institute for General Artificial Intelligence (BIGAI)

• Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents [NeurIPS 2023]

  Zihao Wang1,2 Shaofei Cai1,2 Guanzhou Chen3 Anji Liu4 Xiaojian Ma4 Yitao Liang1,5†

  1Institute for Artificial Intelligence, Peking University, 2School of Intelligence Science and Technology, Peking University, 3School of Computer Science, Beijing University of Posts and Telecommunications, 4Computer Science Department, University of California, Los Angeles, 5Beijing Institute for General Artificial Intelligence (BIGAI)

• CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society [NeurIPS 2023] [Github] [Project page]

Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, Dmitrii Khizbullin, Bernard Ghanem

1King Abdullah University of Science and Technology (KAUST)

• Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents [arXiv 2022] [Github] [Project page]

Wenlong Huang1, Pieter Abbeel1, Deepak Pathak2, Igor Mordatch3

1UC Berkeley, 2Carnegie Mellon University, 3Google

• FILM: Following Instructions in Language with Modular Methods [ICLR 2022] [Github] [Project page]

So Yeon Min1, Devendra Singh Chaplot2, Pradeep Ravikumar1, Yonatan Bisk1, Ruslan Salakhutdinov1

1Carnegie Mellon University 2Facebook AI Research

• Embodied Task Planning with Large Language Models [arXiv 2023] [Github] [Project page] [Demo] [Huggingface Model]

Zhenyu Wu1, Ziwei Wang2,3, Xiuwei Xu2,3, Jiwen Lu2,3, Haibin Yan1*

1School of Automation, Beijing University of Posts and Telecommunications, 2Department of Automation, Tsinghua University, 3Beijing National Research Center for Information Science and Technology

• SPRING: GPT-4 Out-performs RL Algorithms by Studying Papers and Reasoning [arXiv 2023]

Yue Wu1,4* , Shrimai Prabhumoye2 , So Yeon Min1 , Yonatan Bisk1 , Ruslan Salakhutdinov1 ,Amos Azaria3 , Tom Mitchell1 , Yuanzhi Li1,4

1Carnegie Mellon University, 2NVIDIA, 3Ariel University, 4Microsoft Research

• PONI: Potential Functions for ObjectGoal Navigation with Interaction-free Learning [CVPR 2022 (Oral)] [Project page] [Github]

Santhosh Kumar Ramakrishnan1,2, Devendra Singh Chaplot1, Ziad Al-Halah2 Jitendra Malik1,3, Kristen Grauman1,2

1Facebook AI Research, 2UT Austin, 3UC Berkeley

• Moving Forward by Moving Backward: Embedding Action Impact over Action Semantics [ICLR 2023] [Project page] [Github]

Kuo-Hao Zeng1, Luca Weihs2, Roozbeh Mottaghi1, Ali Farhadi1

1Paul G. Allen School of Computer Science & Engineering, University of Washington, 2PRIOR @ Allen Institute for AI

• Modeling Dynamic Environments with Scene Graph Memory [ICML 2023]

Andrey Kurenkov1, Michael Lingelbach1, Tanmay Agarwal1, Emily Jin1, Chengshu Li1, Ruohan Zhang1, Li Fei-Fei1, Jiajun Wu1, Silvio Savarese2, Roberto Mart´ın-Mart´ın3

1Department of Computer Science, Stanford University 2Salesforce AI Research 3Department of Computer Science, University of Texas at Austin.

• Reasoning with Language Model is Planning with World Model [arXiv 2023]

Shibo Hao∗♣, Yi Gu∗♣, Haodi Ma♢, Joshua Jiahua Hong♣, Zhen Wang♣ ♠, Daisy Zhe Wang♢, Zhiting Hu♣

♣UC San Diego, ♢University of Florida, ♠Mohamed bin Zayed University of Artificial Intelligence

• Do As I Can, Not As I Say: Grounding Language in Robotic Affordances [arXiv 2022]

Robotics at Google, Everyday Robots

• Do Embodied Agents Dream of Pixelated Sheep?: Embodied Decision Making using Language Guided World Modelling [ICML 2023]

Kolby Nottingham1 Prithviraj Ammanabrolu2 Alane Suhr2 Yejin Choi3,2 Hannaneh Hajishirzi3,2 Sameer Singh1,2 Roy Fox1

1Department of Computer Science, University of California Irvine 2Allen Institute for Artificial Intelligence 3Paul G. Allen School of Computer Science

• Context-Aware Planning and Environment-Aware Memory for Instruction Following Embodied Agents [ICCV 2023] [Project page]

Byeonghwi Kim Jinyeon Kim Yuyeong Kim1,* Cheolhong Min Jonghyun Choi†

Yonsei University 1Gwangju Institute of Science and Technology

• Inner Monologue: Embodied Reasoning through Planning with Language Models [CoRL 2022] [Project page]

Robotics at Google

• Language Models Meet World Models: Embodied Experiences Enhance Language Models [arXiv 2023] [Twitter]

Jiannan Xiang∗♠, Tianhua Tao∗♠, Yi Gu♠, Tianmin Shu♢, Zirui Wang♠, Zichao Yang♡, Zhiting Hu♠

♠UC San Diego, ♣UIUC, ♢MIT, ♡Carnegie Mellon University

• AlphaBlock: Embodied Finetuning for Vision-Language Reasoning in Robot Manipulation [arXiv 2023] [Video]

Chuhao Jin1* , Wenhui Tan1* , Jiange Yang2* , Bei Liu3† , Ruihua Song1 , Limin Wang2 , Jianlong Fu3†

1Renmin University of China, 2Nanjing University, 3Microsoft Research

• A Persistent Spatial Semantic Representation for High-level Natural Language Instruction Execution [CoRL 2021] [Project page] [Poster]

Valts Blukis1,2, Chris Paxton1, Dieter Fox1,3, Animesh Garg1,4, Yoav Artzi2

1NVIDIA 2Cornell University 3University of Washington 4University of Toronto, Vector Institute

• LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models [ICCV 2023] [Project page] [Github]

Chan Hee Song1, Jiaman Wu1, Clayton Washington1, Brian M. Sadler2, Wei-Lun Chao1, Yu Su1

1The Ohio State University, 2DEVCOM ARL

• Code as Policies: Language Model Programs for Embodied Control [arXiv 2023] [Project page] [Github] [Blog] [Colab]

Jacky Liang, Wenlong Huang, Fei Xia, Peng Xu, Karol Hausman, Brian Ichter, Pete Florence, Andy Zeng

Robotics at Google

• 3D-LLM: Injecting the 3D World into Large Language Models [arXiv 2023]

1Yining Hong, 2Haoyu Zhen, 3Peihao Chen, 4Shuhong Zheng, 5Yilun Du, 6Zhenfang Chen, 6,7Chuang Gan

1UCLA 2 SJTU 3 SCUT 4 UIUC 5 MIT 6MIT-IBM Watson AI Lab 7 Umass Amherst

• VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models [arXiv 2023] [Project page] [Online Demo]

Wenlong Huang1, Chen Wang1, Ruohan Zhang1, Yunzhu Li1,2, Jiajun Wu1, Li Fei-Fei1

1Stanford University 2University of Illinois Urbana-Champaign

• Palm-e: An embodied multimodal language mode [ICML 2023] [Project page]

1Robotics at Google 2TU Berlin 3Google Research

• Large Language Models as Commonsense Knowledge for Large-Scale Task Planning [arXiv 2023]

Zirui Zhao Wee Sun Lee David Hsu

School of Computing National University of Singapore

• An Embodied Generalist Agent in 3D World [ICML 2024]

Jiangyong Huang, Silong Yong, Xiaojian Ma, Xiongkun Linghu, Puhao Li, Yan Wang, Qing Li, Song-Chun Zhu, Baoxiong Jia, Siyuan Huang Beijing Institute for General Artificial Intelligence (BIGAI)

Multi-Agent Learning and Coordination

• Communication-Efficient Desire Alignment for Embodied Agent-Human Adaptation [ACL 2026 (Oral)]

Yuanfei Wang1, Xinju Huang2, Fangwei Zhong2, Yaodong Yang1, Yizhou Wang1, Yuanpei Chen1, Hao Dong1

1Peking University, 2Beijing Normal University

• Building Cooperative Embodied Agents Modularly with Large Language Models [ICLR 2024] [Project page] [Github]

Hongxin Zhang1*, Weihua Du2*, Jiaming Shan3, Qinhong Zhou1, Yilun Du4, Joshua B. Tenenbaum4, Tianmin Shu4, Chuang Gan1,5

1University of Massachusetts Amherst, 2Tsinghua University, 3Shanghai Jiao Tong University, 4MIT, 5MIT-IBM Watson AI Lab

• War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars [arXiv 2023]

Wenyue Hua1*, Lizhou Fan2*, Lingyao Li2, Kai Mei1, Jianchao Ji1, Yingqiang Ge1, Libby Hemphill2, Yongfeng Zhang1

1Rutgers University, 2University of Michigan

• MindAgent: Emergent Gaming Interaction [arXiv 2023]
  Ran Gong1† Qiuyuan Huang2‡ Xiaojian Ma*1 Hoi Vo3 Zane Durante†4 Yusuke Noda3 Zilong Zheng5 Song-Chun Zhu15678 Demetri Terzopoulos1 Li Fei-Fei4 Jianfeng Gao2
  1UCLA; 2Microsoft Research, Redmond; 3Xbox Team, Microsoft; 4Stanford; 5BIGAI; 6PKU; 7THU; 8UCLA

• Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional Curriculum [ICML 2023]

Jigang Kim1,2 Daesol Cho1,2 H. Jin Kim1,3

1Seoul National University, 2Artificial Intelligence Institute of Seoul National University (AIIS), 3Automation and Systems Research Institute (ASRI).

Note: This paper mainly focuses on reinforcement learning for Embodied AI.

• Adaptive Coordination in Social Embodied Rearrangement [ICML 2023]

Andrew Szot1,2 Unnat Jain1 Dhruv Batra1,2 Zsolt Kira2 Ruta Desai1 Akshara Rai1

1Meta AI 2Georgia Institute of Technology.

Vision and Language Navigation

• CANVAS: Commonsense-Aware Navigation System for Intuitive Human-Robot Interaction [ICRA 2025]

Suhwan Choi1 Yongjun Cho1 Minchan Kim1 Jaeyoon Jung1 Myunchul Joe1 Yubeen Park1 Minseo Kim2 Sungwoong Kim2 Sungjae Lee2 Hwiseong Park1 Jiwan Chung2 Youngjae Yu2

1MAUM.AI 2Yonsei University

• IndoorSim-to-OutdoorReal: Learning to Navigate Outdoors without any Outdoor Experience [arXiv 2023]

Joanne Truong1,2, April Zitkovich1, Sonia Chernova2, Dhruv Batra2,3, Tingnan Zhang1, Jie Tan1, Wenhao Yu1

1Robotics at Google 2Georgia Institute of Technology 3Meta AI

• DivScene: Benchmarking LVLMs for Object Navigation with Diverse Scenes and Objects [arXiv 2024] [Project page]

Zhaowei Wang1, Hongming Zhang2, Tianqing Fang1,2, Ye Tian3, Yue Yang4, Kaixin Ma2, Xiaoman Pan2, Yangqiu Song1, Dong Yu2

1CSE Department, HKUST  2Tencent AI Lab, Bellevue, USA  3Robotics X, Tencent  4University of Pennsylvania

• ESC: Exploration with Soft Commonsense Constraints for Zero-shot Object Navigation [ICML 2023]

Kaiwen Zhou1, Kaizhi Zheng1, Connor Pryor1, Yilin Shen2, Hongxia Jin2, Lise Getoor1, Xin Eric Wang1

1University of California, Santa Cruz 2Samsung Research America.

• NavGPT: Explicit Reasoning in Vision-and-Language Navigation with Large Language Models [arXiv 2023]

Gengze Zhou1 Yicong Hong2 Qi Wu1

1The University of Adelaide 2The Australian National University

• Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model [arXiv 2023] [Github]
  Siyuan Huang1,2 Zhengkai Jiang4 Hao Dong3 Yu Qiao2 Peng Gao2 Hongsheng Li5

1Shanghai Jiao Tong University, 2Shanghai AI Laboratory, 3CFCS, School of CS, PKU, 4University of Chinese Academy of Sciences, 5The Chinese University of Hong Kong

Detection

• DetGPT: Detect What You Need via Reasoning [arXiv 2023]

Renjie Pi1∗ Jiahui Gao2* Shizhe Diao1∗ Rui Pan1 Hanze Dong1 Jipeng Zhang1 Lewei Yao1 Jianhua Han3 Hang Xu2 Lingpeng Kong2 Tong Zhang1

1The Hong Kong University of Science and Technology 2The University of Hong Kong 3Shanghai Jiao Tong University

3D Grounding

• LLM-Grounder: Open-Vocabulary 3D Visual Grounding with Large Language Model as an Agent [arXiv 2023]

Jianing Yang1,, Xuweiyi Chen1,, Shengyi Qian1, Nikhil Madaan, Madhavan Iyengar1, David F. Fouhey1,2, Joyce Chai1

1University of Michigan, 2New York University

• 3D-VisTA: Pre-trained Transformer for 3D Vision and Text Alignment [ICCV 2023]

Ziyu Zhu, Xiaojian Ma, Yixin Chen, Zhidong Deng, Siyuan Huang, Qing Li Beijing Institute for General Artificial Intelligence (BIGAI)

Interactive Embodied Learning

• CombatVLA: An Efficient Vision-Language-Action Model for Combat Tasks in 3D Action Role-Playing Games [ICCV 2025] [Project page]

Peng Chen*, Pi Bu*, Yingyao Wang, Xinyi Wang, Ziming Wang, Jie Guo, Yingxiu Zhao, Qi Zhu, Jun Song†, Siran Wang, Jiamang Wang, Bo Zheng

Alibaba Group

• Meta-Control: Automatic Model-based Control System Synthesis for Heterogeneous Robot Skills [CoRL 2024] [Project page]

Tianhao Wei1*, Liqian Ma12*, Rui Chen1, Weiye Zhao1, Changliu Liu1

*Equal Contribution 1Carnegie Mellon University 2Tsinghua University

• Grounding Large Language Models in Interactive Environments with Online Reinforcement Learning [ICML 2023]

Thomas Carta1*, Clement Romac ´1,2, Thomas Wolf2, Sylvain Lamprier3, Olivier Sigaud4, Pierre-Yves Oudeyer1

1Inria (Flowers), University of Bordeaux, 2Hugging Face, 3Univ Angers, LERIA, SFR MATHSTIC, F-49000, 4Sorbonne University, ISIR

• Learning Affordance Landscapes for Interaction Exploration in 3D Environments [NeurIPS 2020] [Project page]

Tushar Nagarajan, Kristen Grauman

UT Austin and Facebook AI Research, UT Austin and Facebook AI Research

• Embodied Question Answering in Photorealistic Environments with Point Cloud Perception [CVPR 2019 (oral)] [Slides]

Erik Wijmans1†, Samyak Datta1, Oleksandr Maksymets2†, Abhishek Das1, Georgia Gkioxari2, Stefan Lee1, Irfan Essa1, Devi Parikh1,2, Dhruv Batra1,2

1Georgia Institute of Technology, 2Facebook AI Research

• Multi-Target Embodied Question Answering [CVPR 2019]

Licheng Yu1, Xinlei Chen3, Georgia Gkioxari3, Mohit Bansal1, Tamara L. Berg1,3, Dhruv Batra2,3

1University of North Carolina at Chapel Hill 2Georgia Tech 3Facebook AI

• Neural Modular Control for Embodied Question Answering [CoRL 2018 (Spotlight)] [Project page] [Github]

Abhishek Das1,Georgia Gkioxari2, Stefan Lee1, Devi Parikh1,2, Dhruv Batra1,2

1Georgia Institute of Technology 2Facebook AI Research

• Embodied Question Answering [CVPR 2018 (oral)] [Project page] [Github]

Abhishek Das1, Samyak Datta1, Georgia Gkioxari22, Stefan Lee1, Devi Parikh2,1, Dhruv Batra2

1Georgia Institute of Technology, 2Facebook AI Research

Rearrangement

• A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search [ICLR 2023]

1Brandon Trabucco, 2Gunnar A Sigurdsson, 2Robinson Piramuthu, 2,3Gaurav S. Sukhatme, 1Ruslan Salakhutdinov

1CMU, 2Amazon Alexa AI, 3University of Southern California

Benchmark

• EmbodiedMemory-Bench: Benchmarking Embodied Memory for Long-Horizon Embodied Tasks [arXiv 2026.09] [Github] [Project Page]

Lizhou Liang, Xinyu Zhong, Miao Pan, Xiaohe Zhou, Xuanyu Liu, Qinfeng Li, Peng Li, Jintao Chen, Xuhong Zhang, and Wenqi Zhang

Zhejiang University, Central South University, Institute of Software, Chinese Academy of Sciences

• NavSpace: How Intelligent Agents Follow Spatial Intelligence Instructions [ICRA 2026] [Github]

Haolin Yang1,2,, Yuxing Long1,2,, Zhuoyuan Yu1,2, Zihan Yang1, Minghan Wang1, Jiapeng Xu1, Yihan Wang1, Ziyan Yu1, Wenzhe Cai3, Lei Kang1, Hao Dong1,2,†

*Equal Contribution †Corresponding author 1CFCS, School of Computer Science, Peking University, 2PrimeBot, 3Shanghai AI Lab

• RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics [Arxiv 2025] [Project Page]

Enshen Zhou1,2,, Jingkun An1,, Cheng Chi2,*

1Beihang University, 2Beijing Academy of Artificial Intelligence

• DivScene: Benchmarking LVLMs for Object Navigation with Diverse Scenes and Objects [arXiv 2024] [Project page]

Zhaowei Wang1, Hongming Zhang2, Tianqing Fang1,2, Ye Tian3, Yue Yang4, Kaixin Ma2, Xiaoman Pan2, Yangqiu Song1, Dong Yu2

1CSE Department, HKUST  2Tencent AI Lab, Bellevue, USA  3Robotics X, Tencent  4University of Pennsylvania

• ReALFRED: An Embodied Instruction Following Benchmark in Photo-Realistic Environments [ECCV 2024] [Project page]

Taewoong Kim1*, Cheolhong Min1*, Byeonghwi Kim1, Jinyeon Kim12, Wonje Jeung1, Jonghyun Choi1

*Equal Contribution 1Seoul National University 2Yonsei University

• Online Continual Learning for Interactive Instruction Following Agents [ICLR 2024] [Project page]

Byeonghwi Kim1*, Minhyuk Seo1*, Jonghyun Choi2

*Equal Contribution 1Yonsei University 2Seoul National University

• SmartPlay: A Benchmark for LLMs as Intelligent Agents [ICLR 2024] [Github]

Yue Wu1,2, Xuan Tang1, Tom Mitchell1, Yuanzhi Li1,2 1Carnegie Mellon University, 2Microsoft Research

• RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation [arXiv 2023] [Project page] [Github]

Yufei Wang1, Zhou Xian1, Feng Chen2, Tsun-Hsuan Wang3, Yian Wang4, Katerina Fragkiadaki1, Zackory Erickson1, David Held1, Chuang Gan4,5

1CMU, 2Tsinghua IIIS, 3MIT CSAIL, 4UMass Amherst, 5MIT-IBM AI Lab

• ALFWorld: Aligning Text and Embodied Environments for Interactive Learning [ICLR 2021] [Project page] [Github]

Mohit Shridhar† Xingdi Yuan♡ Marc-Alexandre Côté♡ Yonatan Bisk‡ Adam Trischler♡ Matthew Hausknecht♣

‡University of Washington ♡Microsoft Research, Montréal ‡Carnegie Mellon University ♣Microsoft Research

• ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks [CVPR 2020] [Project page] [Github]

Mohit Shridhar1 Jesse Thomason1 Daniel Gordon1 Yonatan Bisk1,2,3 Winson Han3 Roozbeh Mottaghi1,3 Luke Zettlemoyer1 Dieter Fox1,4

1Paul G. Allen School of Computer Sci. & Eng., Univ. of Washington, 2Language Technologies Institute @ Carnegie Mellon University, 3Allen Institute for AI, 4NVIDIA

• VIMA: Robot Manipulation with Multimodal Prompts [ICML 2023] [Project page] [Github] [VIMA-Bench]

Yunfan Jiang1 Agrim Gupta1† Zichen Zhang2† Guanzhi Wang3,4† Yongqiang Dou5 Yanjun Chen1 Li Fei-Fei1 Anima Anandkumar3,4 Yuke Zhu3,6‡ Linxi Fan3‡

• SQA3D: Situated Question Answering in 3D Scenes [ICLR 2023] [Project page] [Slides] [Github]

Xiaojian Ma2 Silong Yong1,3* Zilong Zheng1 Qing Li1 Yitao Liang1,4 Song-Chun Zhu1,2,3,4 Siyuan Huang1

1Beijing Institute for General Artificial Intelligence (BIGAI) 2UCLA 3Tsinghua University 4Peking University

• IQA: Visual Question Answering in Interactive Environments [CVPR 2018] [Github] [Demo video (YouTube)]

Danie1 Gordon1 Aniruddha Kembhavi2 Mohammad Rastegari2,4 Joseph Redmon1 Dieter Fox1,3 Ali Farhadi1,2

1Paul G. Allen School of Computer Science, University of Washington 2Allen Institute for Artificial Intelligence 3Nvidia 4Xnor.ai

• Env-QA: A Video Question Answering Benchmark for Comprehensive Understanding of Dynamic Environments [ICCV 2021] [Project page] [Github]

Difei Gao1,2, Ruiping Wang1,2,3, Ziyi Bai1,2, Xilin Chen1,

1Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, 2University of Chinese Academy of Sciences, 3Beijing Academy of Artificial Intelligence

Simulator

• UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AI [ICCV 2025 (Highlight)] [Project page] [Github]

Fangwei Zhong1,6, Kui Wu2, Churan Wang3, Hao Chen4, Hai Ci5, Zhoujun Li2, Yizhou Wang3

1Beijing Normal University, 2Beihang University, 3Peking University, 4City University of Macau, 5National University of Singapore, 6Beijing Institute for General Artificial Intelligence

• LEGENT: Open Platform for Embodied Agents [ACL 2024] [Project page] [Github]

Tsinghua University

• AI2-THOR: An Interactive 3D Environment for Visual AI [arXiv 2022] [Project page] [Github]

Allen Institute for AI, University of Washington, Stanford University, Carnegie Mellon University

• iGibson, a Simulation Environment for Interactive Tasks in Large Realistic Scenes [IROS 2021] [Project page] [Github]

Bokui Shen*, Fei Xia* et al.

• Habitat: A Platform for Embodied AI Research [ICCV 2019] [Project page] [Habitat-Sim] [Habitat-Lab] [Habitat Challenge]

Facebook AI Research, Facebook Reality Labs, Georgia Institute of Technology, Simon Fraser University, Intel Labs, UC Berkeley

• Habitat 2.0: Training Home Assistants to Rearrange their Habitat [NeurIPS 2021] [Project page]

Facebook AI Research, Georgia Tech, Intel Research, Simon Fraser University, UC Berkeley

Others

• Least-to-Most Prompting Enables Complex Reasoning in Large Language Models [ICLR 2023]

Google Research, Brain Team

• React: Synergizing reasoning and acting in language models [ICLR 2023]

Shunyu Yao1∗, Jeffrey Zhao2, Dian Yu2, Nan Du2, Izhak Shafran2, Karthik Narasimhan1, Yuan Cao2

1Department of Computer Science, Princeton University 2, Google Research, Brain team

• Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models [arXiv 2023]

Virginia Tech, Microsoft

• Graph of Thoughts: Solving Elaborate Problems with Large Language Models [arXiv 2023]

ETH Zurich, Cledar, Warsaw University of Technology

• Tree of Thoughts: Deliberate Problem Solving with Large Language Models [arXiv 2023]

Shunyu Yao1, Dian Yu2, Jeffrey Zhao2, Izhak Shafran2, Thomas L. Griffiths1, Yuan Cao2, Karthik Narasimhan1

1Princeton University, 2Google DeepMind

• Chain-of-Thought Prompting Elicits Reasoning in Large Language Models [NeurIPS 2022]

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou

Google Research, Brain Team

• MINEDOJO: Building Open-Ended Embodied Agents with Internet-Scale Knowledge [NeurIPS 2022] [Github] [Project page] [Knowledge Base]

Linxi Fan1 , Guanzhi Wang2∗ , Yunfan Jiang3* , Ajay Mandlekar1 , Yuncong Yang4 , Haoyi Zhu5 , Andrew Tang4 , De-An Huang1 , Yuke Zhu1,6† , Anima Anandkumar1,2†

1NVIDIA, 2Caltech, 3Stanford, 4Columbia, 5SJTU, 6UT Austin

• Distilling Internet-Scale Vision-Language Models into Embodied Agents [ICML 2023]

Theodore Sumers1∗ Kenneth Marino2 Arun Ahuja2 Rob Fergus2 Ishita Dasgupta2

• LISA: Reasoning Segmentation via Large Language Model [arXiv 2023] [Github] [Huggingface Models] [Dataset] [Online Demo]
  TXin Lai1 Zhuotao Tian2 Yukang Chen1 Yanwei Li1 Yuhui Yuan3 Shu Liu2 Jiaya Jia1,2

1The Chinese University of Hong Kong 2SmartMore 3MSRA

• Meta-Control: Automatic Model-based Control System Synthesis for Heterogeneous Robot Skills [CoRL 2024] [Project page]

Tianhao Wei1*, Liqian Ma12*, Rui Chen1, Weiye Zhao1, Changliu Liu1 *Equal Contribution 1Carnegie Mellon University 2Tsinghua University

Acknowledge

Thanks to everyone who has contributed to this repository! Special thanks to those who submitted PRs with solid work—your efforts make this project better and stronger. 🚀✨