mlsanityData to 7 Oct 2026

Grounding Complex Natural Language Commands for Temporal Tasks in Unseen Environments

arXiv 2302.11649 ↗First posted 22 Feb 2023cs.RO cs.AI cs.CLcited by 52

Not on the map. Why?

Abstract (arXiv)

Grounding navigational commands to linear temporal logic (LTL) leverages its unambiguous semantics for reasoning about long-horizon tasks and verifying the satisfaction of temporal constraints. Existing approaches require training data from the specific environment and landmarks that will be used in natural language to understand commands in those environments. We propose Lang2LTL, a modular system and a software package that leverages large language models (LLMs) to ground temporal navigational commands to LTL specifications in environments without prior language data. We comprehensively evaluate Lang2LTL for five well-defined generalization behaviors. Lang2LTL demonstrates the state-of-the-art ability of a single model to ground navigational commands to diverse temporal specifications in 21 city-scaled environments. Finally, we demonstrate a physical robot using Lang2LTL can follow 52 semantically diverse navigational commands in two indoor environments.

Key facts. Cited by 52 papers in the map (data through 7 Oct 2026). Builds on 20 of its 47 references that are in the map. First posted on arXiv 22 Feb 2023.

Builds on

20 of 47 references.

References · 20

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,302
  5. 2022Code as Policies: Language Model Programs for Embodied Controlcited by 1,172
  6. 2022ProgPrompt: Generating Situated Robot Task Plans using Large Language Modelscited by 598
  7. 2022LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Actioncited by 435
  8. 2022Text and Code Embeddings by Contrastive Pre-Trainingcited by 358
  9. 2016Incorporating Copying Mechanism in Sequence-to-Sequence Learningcited by 217
  10. 2020Reward Machines: Exploiting Reward Function Structure in Reinforcement Learningcited by 183
  11. 2018Foundations for Restraining Bolts: Reinforcement Learning with LTLf/LDLf restraining specificationscited by 69
  12. 2017Environment-Independent Task Specifications via GLTLcited by 67
8 more
  1. 2022CAPE: Corrective Actions from Precondition Errors using Large Language Modelscited by 30
  2. 2020Learning a natural-language to LTL executable semantic parser for grounded roboticscited by 22
  3. 2022From Spot 2.0 to Spot 2.10: What's New?cited by 20
  4. 2019Specification Patterns for Robotic Missionscited by 16
  5. 2019Planning With Uncertain Specifications (PUnS)cited by 11
  6. 2020Interactive Robot Training for Non-Markov Taskscited by 9
  7. 2019Planning with State Abstractions for Non-Markovian Task Specificationscited by 8
  8. 2022LTL-Transfer: Skill Transfer for Temporal Task Specificationcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 21; 2025: 16; 2026: 14.

52 papers.

Sort:

By area:

  1. 2024Large Language Models Can Learn Temporal Reasoningcited by 110
  2. 2024Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoningcited by 83
  3. 2025Safety Guardrails for LLM-Enabled Robotscited by 30
  4. 2024Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Modelscited by 27
  5. 2023Are Large Language Models Temporally Grounded?cited by 25
  6. 2024A Survey of Robotic Language Grounding: Tradeoffs between Symbols and Embeddingscited by 23
  7. 2024SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Modelscited by 21
  8. 2024DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RLcited by 20
  9. 2025VeriSafe Agent: Safeguarding Mobile GUI Agent via Logic-based Action Verificationcited by 20
  10. 2025VeriPlan: Integrating Formal Verification and LLMs into End-User Planningcited by 19
  11. 2024SPINE: Online Semantic Planning for Missions with Incomplete Natural Language Specifications in Unstructured Environmentscited by 16
  12. 2025Constrained Discrete Diffusioncited by 16
38 more
  1. 2024Verifiably Following Complex Robot Instructions with Foundation Modelscited by 15
  2. 2025Air-Ground Collaboration for Language-Specified Missions in Unknown Environmentscited by 11
  3. 2024Neuro-Symbolic Evaluation of Text-to-Video Models using Formal Verificationcited by 9
  4. 2025ConformalNL2LTL: Translating Natural Language Instructions into Temporal Logic Formulas with Conformal Correctness Guaranteescited by 9
  5. 2024Generative AI Agents in Autonomous Machines: A Safety Perspectivecited by 7
  6. 2024Pragmatic Embodied Spoken Instruction Following in Human-Robot Collaboration with Theory of Mindcited by 6
  7. 2025Grammar-Forced Translation of Natural Language to Temporal Logic using LLMscited by 6
  8. 2024Joint Verification and Refinement of Language Models for Safety-Constrained Planningcited by 5
  9. 2025LogicGuard: Improving Embodied LLM agents through Temporal Logic based Criticscited by 5
  10. 2025Ground-Compose-Reinforce: Grounding Language in Agentic Behaviours using Limited Datacited by 5
  11. 2024Closed Loop Interactive Embodied Reasoning for Robot Manipulationcited by 4
  12. 2024LTLBench: Towards Benchmarks for Evaluating Temporal Reasoning in Large Language Modelscited by 4
  13. 2024Jailbreaking LLM-Controlled Robotscited by 4
  14. 2025Verifiable Natural Language to Linear Temporal Logic Translation: A Benchmark Dataset and Evaluation Suitecited by 4
  15. 2024CoT-TL: Low-Resource Temporal Knowledge Representation of Planning Instructions Using Chain-of-Thought Reasoningcited by 3
  16. 2025Contrastive Learning from Exploratory Actions: Leveraging Natural Interactions for Preference Elicitationcited by 3
  17. 2025TRAVEL: Training-Free Retrieval and Alignment for Vision-and-Language Navigationcited by 3
  18. 2024Towards No-Code Programming of Cobots: Experiments with Code Synthesis by Large Code Models for Conversational Programmingcited by 2
  19. 2024The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcarecited by 2
  20. 2025Beyond Fixed Tasks: Unsupervised Environment Design for Task-Level Pairscited by 2
  21. 2025Synthesizing Precise Protocol Specs from Natural Language for Effective Test Generationcited by 2
  22. 2026VASO: Formally Verifiable Self-Evolving Skills for Physical AI Agentscited by 2
  23. 2024SYNAPSE: SYmbolic Neural-Aided Preference Synthesis Enginecited by 1
  24. 2025HiBerNAC: Hierarchical Brain-inspired Robotic Neural Agent Collective for Disentangling Complex Manipulationcited by 1
  25. 2026Structural-Ambiguity-Aware Translation from Natural Language to Signal Temporal Logiccited by 1
  26. 2024Nl2Hltl2Plan: Scaling Up Natural Language Understanding for Multi-Robots Through Hierarchical Temporal Logic Task Representationcited by 0
  27. 2024Creating and Repairing Robot Programs in Open-World Domainscited by 0
  28. 2025GinSign: Grounding Natural Language Into System Signatures for Temporal Logic Translationcited by 0
  29. 2026TempViz: On the Evaluation of Temporal Knowledge in Text-to-Image Modelscited by 0
  30. 2026U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planningcited by 0
  31. 2026Robust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learningcited by 0
  32. 2026Natural Synthesis: Outperforming Reactive Synthesis Tools with Large Reasoning Modelscited by 0
  33. 2026NeuroNL2LTL: A Neurosymbolic Framework for Natural Language Translation of Linear Temporal Logiccited by 0
  34. 2026WIRE: Profiling Witnessed Within-Policy Instruction Collisions in LLM Agentscited by 0
  35. 2026Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skillscited by 0
  36. 2026Symbolic Temporal Supervision of LLM Agents Using Contractscited by 0
  37. 2026Bayesian Active Learning for Intent Disambiguation in Interactive Robot Planningcited by 0
  38. 2026Video2STL: Grounding VLM-Generated Temporal Specifications for Robot Learningcited by 0

50 most cited of 52 All 52 (JSON)