Kairos: Grounded Forecasting of Presence and Directional Flow in 4D Scene Graphs

arXiv:2609.27467 · cs.RO, cs.AI · Submitted 2026-09-23 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-09-23

Updated: 2026-09-23

Code: https://github.com/IacopomC/kairos

Terminology

• Archetype — 8× in this paper · explained in 1 episode
• Abstraction — 6× in this paper · explained in 1 episode
• Calibration — 6× in this paper · explained in 7 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Grounding — 5× in this paper · explained in 3 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Robustness — 3× in this paper · explained in 5 episodes
• Affordance — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Expected Calibration Error — 2× in this paper
• Mean Log Predictive Probability — 2× in this paper
• Alignment Scores — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Circular Continuous Ranked Probability Score — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Empirical Coverage — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Mean Log Predictive Density — 1× in this paper
• Non-Uniform Discrete Fourier Transform — 1× in this paper
• Speed Mean Absolute Error — 1× in this paper
• Task Planning — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations
• Data-driven physics-based modeling of pedestrian dynamics

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