Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks
On the map: LLM reasoning → Spatial and embodied reasoning
Abstract (arXiv)
Recent advances in deep thinking models have demonstrated remarkable reasoning capabilities on mathematical and coding tasks. However, their effectiveness in embodied domains which require continuous interaction with environments through image action interleaved trajectories remains largely -unexplored. We present Embodied Reasoner, a model that extends o1 style reasoning to interactive embodied search tasks. Unlike mathematical reasoning that relies primarily on logical deduction, embodied scenarios demand spatial understanding, temporal reasoning, and ongoing self-reflection based on interaction history. To address these challenges, we synthesize 9.3k coherent Observation-Thought-Action trajectories containing 64k interactive images and 90k diverse thinking processes (analysis, spatial reasoning, reflection, planning, and verification). We develop a three-stage training pipeline that progressively enhances the model's capabilities through imitation learning, self-exploration via rejection sampling, and self-correction through reflection tuning. The evaluation shows that our model significantly outperforms those advanced visual reasoning models, e.g., it exceeds OpenAI o1, o3-mini, and Claude-3.7 by +9%, 24%, and +13%. Analysis reveals our model exhibits fewer repeated searches and logical inconsistencies, with particular advantages in complex long-horizon tasks. Real-world environments also show our superiority while exhibiting fewer repeated searches and logical inconsistency cases.
Key facts. Cited by 44 papers in the map (data through 14 Oct 2026). Placed in Spatial and embodied reasoning, one of 17 directions in LLM reasoning. Builds on 103 of its 133 references that are in the map. First posted on arXiv 27 Mar 2025.
Builds on
103 of 133 references.
Closest ancestors · 7
Same direction, newest first
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- 2024NavCoT: Boosting LLM-Based Vision-and-Language Navigation via Learning Disentangled Reasoning12 Mar
- 2023See and Think: Embodied Agent in Virtual Environment26 Nov
- 2023EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought24 May
- 2023Collaborating with language models for embodied reasoning1 Feb
- 2022Inner Monologue: Embodied Reasoning through Planning with Language Models12 Jul
Other references · 96
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- 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,371
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- 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,348
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- 2024Octo: An Open-Source Generalist Robot Policycited by 1,484
- 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,376
- 2022Code as Policies: Language Model Programs for Embodied Controlcited by 1,210
- 2025Kimi k1.5: Scaling Reinforcement Learning with LLMscited by 1,210
- 2019Habitat: A Platform for Embodied AI Researchcited by 1,191
- 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,035
- 2017Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environmentscited by 1,027
- 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 869
- 2019ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Taskscited by 783
- 2023Multimodal Chain-of-Thought Reasoning in Language Modelscited by 752
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- 2020Beyond the Nav-Graph: Vision-and-Language Navigation in Continuous Environmentscited by 441
- 2022LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Actioncited by 439
- 2022ProcTHOR: Large-Scale Embodied AI Using Procedural Generationcited by 380
- 2016Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learningcited by 366
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- 2023An Embodied Generalist Agent in 3D Worldcited by 365
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- 2023A Survey on Multimodal Large Language Models for Autonomous Drivingcited by 290
- 2021History Aware Multimodal Transformer for Vision-and-Language Navigationcited by 271
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- 2024Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systemscited by 164
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- 2023SMART-LLM: Smart Multi-Agent Robot Task Planning using Large Language Modelscited by 153
- 2025LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMscited by 147
50 most cited of 96 All 96 (JSON)
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Citing papers per year: 2025: 29; 2026: 15.
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- 2025ESearch-R1: Learning Cost-Aware MLLM Agents for Interactive Embodied Search via Reinforcement Learning21 Dec 2025
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12 newest of 21 All 21 (JSON)
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- 2026Why MLLMs Struggle to Determine Object Orientations14 Apr 2026
- 2026Explore with Long-term Memory: A Benchmark and Multimodal LLM-based Reinforcement Learning Framework for Embodied Exploration11 Jan 2026
- 2025BEAT: Visual Backdoor Attacks on VLM-based Embodied Agents via Contrastive Trigger Learning31 Oct 2025
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- 2025LookPlanGraph: Embodied Instruction Following Method with VLM Graph Augmentation24 Dec 2025
- 2025Flowing from Reasoning to Motion: Learning 3D Hand Trajectory Prediction from Egocentric Human Interaction Videos18 Dec 2025
- 2025ArtiBench and ArtiBrain: Benchmarking Generalizable Vision-Language Articulated Object Manipulation25 Nov 2025
- 2025Robix: A Unified Model for Robot Interaction, Reasoning and Planning1 Sep 2025
- 2025M3DMap: Object-aware Multimodal 3D Mapping for Dynamic Environments23 Aug 2025
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