Meta-Ctrl: Guaranteed Plan Generation by Decoupling Syntactic and Semantic Constraints

arXiv:2608.22149 · cs.RO, cs.AI · Submitted 2026-08-23 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-08-23

Updated: 2026-08-28

Project page: https://meta-ctrlg.github.io

Terminology

• Benchmark — 37× in this paper · explained in 2 episodes
• Affordance — 19× in this paper · explained in 1 episode
• Hallucination — 18× in this paper · explained in 3 episodes
• Subgoal Decomposition — 11× in this paper
• Action Sequencing — 10× in this paper
• RAG — 9× in this paper · explained in 3 episodes
• Decoupling — 5× in this paper · explained in 2 episodes
• Embodied Agent Interface — 5× in this paper
• Tokenization — 5× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Grounding — 3× in this paper · explained in 3 episodes
• Admissibility — 2× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Motion Primitives — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
• ProgPrompt: Generating Situated Robot Task Plans using Large Language Models
• Inner Monologue: Embodied Reasoning through Planning with Language Models
• Voyager: An Open-Ended Embodied Agent with Large Language Models
• LLM+P: Empowering Large Language Models with Optimal Planning Proficiency
• Synchromesh: Reliable code generation from pre-trained language models
• Efficient Guided Generation for Large Language Models
• The Llama 3 Herd of Models
• gpt-oss-120b & gpt-oss-20b Model Card
• GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training

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