Feedback Makes Perfect: A Closed-Loop Framework for NL-to-STL Translation
cs.AI, cs.RO, cs.SY, eess.SY
Submitted: 2026-09-27
Updated: 2026-09-27
Terminology
Sources
- ClarifySTL: An Interactive LLM Agent Framework for STL Transformation through Requirements Clarification
- Grounding Complex Natural Language Commands for Temporal Tasks in Unseen Environments
- Data-Efficient Learning of Natural Language to Linear Temporal Logic Translators for Robot Task Specification
- SCP-NL2TL: Selective Conformal Prediction with Semantic Verification for Natural Language to Temporal Logic Specifications
- ReasonSTL: Bridging Natural Language and Signal Temporal Logic via Tool-Augmented Process-Rewarded Learning
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
- VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection