Robotic value models assess task execution from visual observations and instructions, providing feedback for policy learning and execution monitoring. We introduce RoboValue, a fine-grained sim-and-real benchmark for unified evaluation of robotic value models. Its framework evaluates four complementary capability dimensions through shared interfaces: task-state understanding, temporal progress monitoring, failure and recovery reasoning, and value consistency. Diagnostic trajectories and instruction variations test whether value judgments accurately reflect task requirements and changes throughout execution.
The chart will appear after repeat observations. The current metric comes from the source.
21 source votesReal observations only. History before source connection is not reconstructed.
This benchmark can be used for more accurate evaluation of robotic value models, which is important for improving the reliability of feedback in robot control tasks.
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