Labs机构 › Allen Institute for AI (Ai2)艾伦人工智能研究所（Ai2）
Allen Institute for AI (Ai2) · embodied AI & robot learning艾伦人工智能研究所（Ai2） · 具身智能与机器人学习
7 curated papers, code, datasets and hardware from Allen Institute for AI (Ai2) (6 with code), with one-line takeaways.7 个来自艾伦人工智能研究所（Ai2）的精选论文、代码、数据集与硬件（6 个附代码），均配一句话要点。
Labs are matched from each entry's affiliation field by simple name rules (data/labs.yaml); joint work appears under every lab named. Only curated entries are listed, because daily arXiv papers carry no affiliations.机构由每个条目的机构字段按名称规则匹配（data/labs.yaml），合作工作会出现在所有署名机构下。仅列出精选条目，因为每日 arXiv 论文不含机构信息。
Photorealistic interactive indoor scenes where agents open, pick up and change objects; the base of many embodied-AI benchmarks such as ALFRED.具有可交互物体的逼真室内场景，智能体可开关、拾取和改变物体，是 ALFRED 等众多具身智能基准的基础。
@misc{kolve2017ai,
title = {{AI2-THOR: An Interactive 3D Environment for Visual AI}},
author = {Eric Kolve and Roozbeh Mottaghi and Winson Han and Eli VanderBilt and Luca Weihs and Alvaro Herrasti and Matt Deitke and Kiana Ehsani and Daniel Gordon and Yuke Zhu and Aniruddha Kembhavi and Abhinav Gupta and Ali Farhadi},
year = {2017},
eprint = {1712.05474},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/1712.05474},
}
Fully open successor to MolmoAct: a flow-matching action expert on an embodied-reasoning VLM, the OpenFAST tokenizer and a 720 h bimanual YAM dataset; reports beating π0.5 on 7 sim and real benchmarks.MolmoAct 的全开源后继：在具身推理 VLM（MolmoER）上挂接流匹配连续动作专家，并发布开源动作分词器 OpenFAST 与 720 小时双臂 YAM 遥操作数据集；论文报告在 7 个仿真与真机基准上超过 π0.5 等基线，权重、训练代码与数据全部开放。
@misc{fang2026molmoact,
title = {{MolmoAct2: Action Reasoning Models for Real-world Deployment}},
author = {Haoquan Fang and Jiafei Duan and Donovan Clay and Sam Wang and Shuo Liu and Weikai Huang and Xiang Fan and Wei-Chuan Tsai and Shirui Chen and Yi Ru Wang and Shanli Xing and Jaemin Cho and Jae Sung Park and Ainaz Eftekhar and Peter Sushko and Karen Farley and Angad Wadhwa and Cole Harrison and Winson Han and Ying-Chun Lee and Eli VanderBilt and Rose Hendrix and Suveen Ellawela and Lucas Ngoo and Joyce Chai and Zhongzheng Ren and Ali Farhadi and Dieter Fox and Ranjay Krishna},
year = {2026},
eprint = {2605.02881},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2605.02881},
}
CoRL 2026 Oral. Argues simulation can be enough: large, diverse synthetic data gives zero-shot real transfer for static and mobile manipulation. MolmoBot-Engine is an open procedural data pipeline.CoRL 2026 Oral。挑战“仅靠仿真不够”的观点：足够大规模、多样的合成数据即可零样本迁移到真实静态与移动操作。MolmoBot-Engine 是开源的程序化数据管线。
@misc{deshpande2026molmob,
title = {{MolmoB0T: Large-Scale Simulation Enables Zero-Shot Manipulation}},
author = {Abhay Deshpande and Maya Guru and Rose Hendrix and Snehal Jauhri and Ainaz Eftekhar and Rohun Tripathi and Max Argus and Jordi Salvador and Haoquan Fang and Matthew Wallingford and Wilbert Pumacay and Yejin Kim and Quinn Pfeifer and Ying-Chun Lee and Piper Wolters and Omar Rayyan and Mingtong Zhang and Jiafei Duan and Karen Farley and Winson Han and Eli Vanderbilt and Dieter Fox and Ali Farhadi and Georgia Chalvatzaki and Dhruv Shah and Ranjay Krishna},
year = {2026},
eprint = {2603.16861},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2603.16861},
}
Benchmark built on a taxonomy of commonsense reasoning (occlusion, containment, affordances). Reports zero-shot policies dropping over 50% as distractors grow and acting on the wrong object 30% of the time in clutter.基于常识推理分类法（遮挡、容纳、支撑、可供性、隐藏物体）构建的操作基准。报告零样本通用策略在干扰物增多时成功率下降超过 50%，在杂乱场景中约 30% 的时间作用于错误物体，抓取正确部位的比例仅约一半。
@misc{guru2026molmospaces,
title = {{MolmoSpaces-CommonSense: Evaluating Commonsense in Robotic Manipulation Policies}},
author = {Arjun Guru and Max Argus and Jae Sung Park and Jiafei Duan and Ali Farhadi and Ranjay Krishna},
year = {2026},
eprint = {2610.41377},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2610.41377},
}
An open 7B VLA that first outputs depth-aware perception tokens, then an editable 2D trajectory, then actions; reports 70.5% zero-shot on SimplerEnv and 86.6% on LIBERO, with weights, code and data released.开源 7B VLA，先输出深度感知 token，再生成可编辑的二维轨迹，最后输出动作；论文报告 SimplerEnv 零样本 70.5%、LIBERO 86.6%，并开放权重、代码和数据。
@misc{lee2025molmoact,
title = {{MolmoAct: Action Reasoning Models that can Reason in Space}},
author = {Jason Lee and Jiafei Duan and Haoquan Fang and Yuquan Deng and Shuo Liu and Boyang Li and Bohan Fang and Jieyu Zhang and Yi Ru Wang and Sangho Lee and Winson Han and Wilbert Pumacay and Angelica Wu and Rose Hendrix and Karen Farley and Eli VanderBilt and Ali Farhadi and Dieter Fox and Ranjay Krishna},
year = {2025},
eprint = {2508.07917},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2508.07917},
}
@misc{pumacay2024colosseum,
title = {{THE COLOSSEUM: A Benchmark for Evaluating Generalization for Robotic Manipulation}},
author = {Wilbert Pumacay and Ishika Singh and Jiafei Duan and Ranjay Krishna and Jesse Thomason and Dieter Fox},
year = {2024},
eprint = {2402.08191},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2402.08191},
}
800K+ annotated 3D object models; widely used to populate simulators with diverse objects for grasping, rearrangement and procedural scene generation (Objaverse-XL extends it to 10M+).80 万+ 带标注的 3D 物体模型，常用于为仿真器填充多样物体，用于抓取、重排和程序化场景生成（Objaverse-XL 扩展到 1000 万+）。
@misc{deitke2022objaverse,
title = {{Objaverse: A Universe of Annotated 3D Objects}},
author = {Matt Deitke and Dustin Schwenk and Jordi Salvador and Luca Weihs and Oscar Michel and Eli VanderBilt and Ludwig Schmidt and Kiana Ehsani and Aniruddha Kembhavi and Ali Farhadi},
year = {2022},
eprint = {2212.08051},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2212.08051},
}