GraphPoint: Semantic Entity Graphs and Point Trajectories for Compositional Robot Manipulation

arXiv:2609.18358 · cs.RO · Submitted 2026-09-16 · Read on arXiv

cs.RO

Submitted: 2026-09-16

Updated: 2026-09-19

Terminology

• Actor — 13× in this paper · explained in 3 episodes
• Benchmark — 9× in this paper · explained in 2 episodes
• Generalization — 9× in this paper · explained in 13 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Embeddings — 4× in this paper · explained in 2 episodes
• Action Chunking — 2× in this paper · explained in 1 episode
• Compose by Focus — 2× in this paper
• Grounding — 2× in this paper · explained in 3 episodes
• AND PROGRESS RATE — 1× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Action Chunking with Transformers — 1× in this paper
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Compositional Generalization — 1× in this paper · explained in 4 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• M OD SUCCESS RATE — 1× in this paper
• Point Clouds — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes
• Vision-Language Model (VLM) — 1× in this paper · explained in 3 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Point Bridge: 3D Representations for Cross Domain Policy Learning
• Compose by Focus: Scene Graph-based Atomic Skills
• robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
• TAPNext++: What's Next for Tracking Any Point (TAP)?

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