SAGE: Symbolic Action-Gating and Editing for LLM Task Planners

arXiv:2609.34268 · cs.RO, cs.AI · Submitted 2026-09-28 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/mtbui2010/sage

Terminology

• Verifier — 42× in this paper · explained in 2 episodes
• Benchmark — 32× in this paper · explained in 2 episodes
• Verification — 8× in this paper · explained in 2 episodes
• Grounding — 7× in this paper · explained in 3 episodes
• Affordance — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Hallucination — 3× in this paper · explained in 4 episodes
• Symbolic Action-Gating and Editing — 3× in this paper
• Task Planning — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Conference on Robot Learning — 2× in this paper
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Ontology — 2× in this paper · explained in 2 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Adaptive Planning — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Failure Taxonomy — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 1× in this paper
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Korea Electronics Technology Institute — 1× in this paper
• World Model — 1× in this paper · explained in 7 episodes

Sources

• AI2-THOR: An Interactive 3D Environment for Visual AI
• LLM+P: Empowering Large Language Models with Optimal Planning Proficiency
• Learning to Guide Human Experts via Personalized Large Language Models
• Large language model-based task planning for service robots: A review
• Teaching LLMs to Plan: Logical Chain-of-Thought Instruction Tuning for Symbolic Planning

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