ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop
- Published
- Source
- arXiv
- Paper number
- 207
- Field
- Computer Vision
- arXiv ID
- 2605.18746
Key points
- Directional bias: AI models often show confirmation bias, repeatedly choosing actions that confirm their initial impression rather than exploring new information, even though that initial impression may be wrong, and they often commit to an answer early in the process with high confidence regardless of whether the evidence is sufficient.
- Intelligent action planning: Develop an agent that can plan specialized trajectories to resolve spatial uncertainty.
- Uncertainty management and calibration: Build a model that can understand when it does not have enough information and adjust its confidence accordingly.
Paper links
External research summaries. These are not HDATF publications or measured product results.