Ego2World compiles egocentric cooking videos into executable planning environments, where six planners on 105 tasks often had accepted operations leave goals unmet
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Synopsis
The authors introduce Ego2World, a benchmark that compiles annotated cooking activities into executable planning environments under partial observation, linking source steps and objects to symbolic action rules, persistent world states, and explicit task conditions while maintaining world state and agent belief separately; evaluating six planners on 105 tasks shows accepted operations often leave task goals unmet, and 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.
Figure 1: From activity evidence to interactive evaluation. The upper panel illustrates construction: its hidden graph G h G_{h} is denoted G w G^{\mathrm{w}} in the text, and skills correspond to action groups. The lower schematic shows how agents use the compiled environment. Source links, action records, and task checks make decisions inspectable; Table 1 follows a real task through these stages.
arXivInterpretation
Ego2World compiles annotated cooking activities into executable planning environments under partial observation, with a compiler that 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. Relative to egocentric video data that only records human activity, this work turns recorded human activity into an executable environment whose outcomes can be checked, supporting evaluation of the consequences of actions an agent chooses itself. The abstract states that the benchmark comprises a compiler, symbolic action rules, persistent world states, and explicit task conditions, and that it supports executing an agent's proposed actions and checking outcomes; compilation details and data scale are not given in the abstract.
World state and agent belief are maintained separately, enabling controlled studies of planning and information reuse across continuing tasks. Separating world state from belief lets researchers examine the gap between an agent's representation of the environment and the actual state, rather than only final task success. The abstract explicitly states that the two are maintained separately and used for controlled studies; the separation mechanism and experimental design details are not expanded in the abstract.
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. This moves evaluation beyond whether an operation is accepted toward whether the goal is actually attained, and provides traces and condition checks that separate different forms of failure. The abstract reports six planners, 105 tasks, and three distinguishable cases; per-planner numbers and statistical comparisons are not given in the abstract.
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%, while token use is higher and no completion gain is detected. The paired study quantifies separately how persistent belief affects action validity and observation demand, showing that improved validity and fewer visual queries do not automatically translate into higher task completion. The abstract gives specific percentage changes for the paired study and states that token use was higher and no completion gain was detected; sample size and statistical test details are not given in the abstract.
Perspective
The work targets researchers who need to evaluate the consequences of an agent's self-chosen actions, and it applies to studies of planning and information reuse across continuing tasks under partial observation, especially annotated everyday activities such as egocentric cooking. Its executable environments, symbolic action rules, persistent world states, and explicit task conditions let researchers execute an agent's proposed actions and check outcomes, and use execution traces and condition checks to distinguish interrupted runs, partial attainment, and completed execution without goal attainment. The paired Qwen-Plus study further indicates that persistent belief raises action validity and reduces visual-query attempts while incurring higher token use, so the testbed is suited to examining how planning and memory choices affect execution, observation demand, and task attainment.
The abstract does not describe the compiler implementation, how task conditions are defined, the composition and difficulty distribution of the 105 tasks, or per-planner results and statistical tests. The sample size, pairing scheme, and magnitude of token-use increase in the paired Qwen-Plus study are also not given in the abstract. In addition, the abstract mentions no detected completion gain but does not state how that conclusion was tested or its confidence level. Because the reading scope here is the abstract only, these details need to be confirmed in the original text.