Ego2World: Compiling Egocentric Cooking Videos into Executable Worlds for Belief-State Planning
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Abstract (arXiv)
Egocentric videos capture how people carry out everyday activities, yet testing an agent requires evaluating the consequences of actions it chooses itself. We introduce Ego2World, a benchmark that turns annotated cooking activities into executable planning environments under partial observation. Its compiler links source steps and objects to symbolic action rules, persistent world states, and explicit task conditions, so researchers can execute an agent's proposed actions and check their outcomes. World state and agent belief are maintained separately, enabling controlled studies of planning and information reuse across continuing tasks. Evaluating six planners on 105 tasks shows that accepted operations often leave task goals unmet. Execution traces and condition checks distinguish interrupted runs, partial attainment, and completed execution without goal attainment. In a separate paired Qwen-Plus study, persistent belief improves action validity by 4.15 percentage points and reduces visual-query attempts by 90.27%, with higher token use and no detected completion gain. Ego2World provides a reusable testbed for tracing how planning and memory choices affect execution, observation demand, and task attainment, connecting recorded human activity to the development and evaluation of interactive agents.
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References · 17
- 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,348
- 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,556
- 2022Inner Monologue: Embodied Reasoning through Planning with Language Modelscited by 1,081
- 2017AI2-THOR: An Interactive 3D Environment for Visual AIcited by 869
- 2018Scaling Egocentric Vision: The EPIC-KITCHENS Datasetcited by 795
- 2019ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Taskscited by 783
- 2020Rescaling Egocentric Visioncited by 540
- 2018VirtualHome: Simulating Household Activities via Programscited by 415
- 2023SayPlan: Grounding Large Language Models using 3D Scene Graphs for Scalable Robot Task Planningcited by 294
- 2024Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Makingcited by 144
- 2022EgoTaskQA: Understanding Human Tasks in Egocentric Videoscited by 115
- 2025HD-EPIC: A Highly-Detailed Egocentric Video Datasetcited by 104
5 more
- 2024EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarioscited by 41
- 2024VidEgoThink: Assessing Egocentric Video Understanding Capabilities for Embodied AIcited by 34
- 2025ECBench: Can Multi-modal Foundation Models Understand the Egocentric World? A Holistic Embodied Cognition Benchmarkcited by 19
- 2025ENACT: Evaluating Embodied Cognition with World Modeling of Egocentric Interactioncited by 15
- 2026MEMORA: Embodied Action Memory from Egocentric Videos for Reasoning and Planningcited by 4
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