Just-In-Time Scene Graph Growth: Combating Perceptual Saturation in Long-Horizon Robotics

Jul 16, 2026

Researchers introduce JITOMA, a closed-loop framework for constructing 3D scene graphs on demand in long-horizon robotics tasks. JITOMA uses a task heatmap to filter observations and leverages a large language model to dynamically activate only task-relevant anchors, reducing the size of the active scene graph and lowering captioning latency. The approach is evaluated on the new JITOMA-Bench benchmark, demonstrating stable processing times even during frequent task switching.

Why it matters: This work offers a novel solution to perceptual saturation in robotics, enabling more efficient and scalable real-time scene understanding for long-duration tasks.

Full story at: arXiv Computer Vision ↗