mlsanityData to 7 Oct 2026

SayCanPay: Heuristic Planning with Large Language Models using Learnable Domain Knowledge

arXiv 2308.12682 ↗First posted 24 Aug 2023cs.AIcited by 49

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Abstract (arXiv)

Large Language Models (LLMs) have demonstrated impressive planning abilities due to their vast "world knowledge". Yet, obtaining plans that are both feasible (grounded in affordances) and cost-effective (in plan length), remains a challenge, despite recent progress. This contrasts with heuristic planning methods that employ domain knowledge (formalized in action models such as PDDL) and heuristic search to generate feasible, optimal plans. Inspired by this, we propose to combine the power of LLMs and heuristic planning by leveraging the world knowledge of LLMs and the principles of heuristic search. Our approach, SayCanPay, employs LLMs to generate actions (Say) guided by learnable domain knowledge, that evaluates actions' feasibility (Can) and long-term reward/payoff (Pay), and heuristic search to select the best sequence of actions. Our contributions are (1) a novel framing of the LLM planning problem in the context of heuristic planning, (2) integrating grounding and cost-effective elements into the generated plans, and (3) using heuristic search over actions. Our extensive evaluations show that our model surpasses other LLM planning approaches.

Key facts. Cited by 49 papers in the map (data through 7 Oct 2026). Builds on 31 of its 40 references that are in the map. First posted on arXiv 24 Aug 2023.

Builds on

31 of 40 references.

References · 31

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  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. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  5. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
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  8. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 2,993
  9. 2019Fine-Tuning Language Models from Human Preferencescited by 2,124
  10. 2020Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problemscited by 1,873
  11. 2022GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformerscited by 1,838
  12. 2018Averaging Weights Leads to Wider Optima and Better Generalizationcited by 1,194
19 more
  1. 2022Code as Policies: Language Model Programs for Embodied Controlcited by 1,172
  2. 2022Inner Monologue: Embodied Reasoning through Planning with Language Modelscited by 1,057
  3. 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,029
  4. 2021CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generationcited by 890
  5. 2022LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scalecited by 881
  6. 2023Reasoning with Language Model is Planning with World Modelcited by 846
  7. 2022ProgPrompt: Generating Situated Robot Task Plans using Large Language Modelscited by 598
  8. 2023LLM+P: Empowering Large Language Models with Optimal Planning Proficiencycited by 496
  9. 2018VirtualHome: Simulating Household Activities via Programscited by 411
  10. 2020Transporter Networks: Rearranging the Visual World for Robotic Manipulationcited by 342
  11. 2021Generative Spoken Language Modeling from Raw Audiocited by 336
  12. 2023Reward Design with Language Modelscited by 257
  13. 2023Text2Motion: From Natural Language Instructions to Feasible Planscited by 223
  14. 2022A Survey of Vision-Language Pre-Trained Modelscited by 177
  15. 2023Translating Natural Language to Planning Goals with Large-Language Modelscited by 132
  16. 2023On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)cited by 85
  17. 2023Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agentscited by 66
  18. 2022Plansformer: Generating Symbolic Plans using Transformerscited by 41
  19. 2022Planning in Observable POMDPs in Quasipolynomial Timecited by 25

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 14; 2025: 26; 2026: 8.

49 papers.

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  1. 2024Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planningcited by 95
  2. 2025PlanGenLLMs: A Modern Survey of LLM Planning Capabilitiescited by 82
  3. 2025AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-benchcited by 65
  4. 2024On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)cited by 40
  5. 2025CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agentscited by 32
  6. 2024REvolve: Reward Evolution with Large Language Models using Human Feedbackcited by 22
  7. 2024SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Modelscited by 21
  8. 2024Trust the PRoC3S: Solving Long-Horizon Robotics Problems with LLMs and Constraint Satisfactioncited by 19
  9. 2024Hallucination Detection in Foundation Models for Decision-Making: A Flexible Definition and Review of the State of the Artcited by 17
  10. 2025Have Large Language Models Learned to Reason? A Characterization via 3-SAT Phase Transitioncited by 13
  11. 2025EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Associationcited by 10
  12. 2024LASP: Surveying the State-of-the-Art in Large Language Model-Assisted AI Planningcited by 9
37 more
  1. 2025PhotoArtAgent: Intelligent Photo Retouching with Language Model-Based Artist Agentscited by 9
  2. 2025Optimizing Prompt Sequences using Monte Carlo Tree Search for LLM-Based Optimizationcited by 9
  3. 2024A Theory of Response Sampling in LLMs: Part Descriptive and Part Prescriptivecited by 8
  4. 2024Language Models can Infer Action Semantics for Symbolic Planners from Environment Feedbackcited by 8
  5. 2024Tulip Agent -- Enabling LLM-Based Agents to Solve Tasks Using Large Tool Librariescited by 7
  6. 2025Exploratory Retrieval-Augmented Planning For Continual Embodied Instruction Followingcited by 7
  7. 2025Hephaestus: Improving Fundamental Agent Capabilities of Large Language Models through Continual Pre-Trainingcited by 6
  8. 2025World Model Implanting for Test-time Adaptation of Embodied Agentscited by 5
  9. 2025Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmapcited by 5
  10. 2025End-to-end PDDL Planning with Hardcoded and Dynamic Agentscited by 5
  11. 2023Planning with Logical Graph-based Language Model for Instruction Generationcited by 4
  12. 2025Tru-POMDP: Task Planning Under Uncertainty via Tree of Hypotheses and Open-Ended POMDPscited by 4
  13. 2024HBTP: Heuristic Behavior Tree Planning with Large Language Model Reasoningcited by 3
  14. 2024DM2RM: Dual-Mode Multimodal Ranking for Target Objects and Receptacles Based on Open-Vocabulary Instructionscited by 3
  15. 2025Position: Agentic Systems Constitute a Key Component of Next-Generation Intelligent Image Processingcited by 3
  16. 2025EmboMatrix: A Scalable Training-Ground for Embodied Decision-Makingcited by 3
  17. 2025Exploring 3D Reasoning-Driven Planning: From Implicit Human Intentions to Route-Aware Activity Planningcited by 2
  18. 2025Learning Admissible Heuristics for A*: Theory and Practicecited by 2
  19. 2026Test-Time Mixture of World Models for Embodied Agents in Dynamic Environmentscited by 2
  20. 2024RAG-Modulo: Solving Sequential Tasks using Experience, Critics, and Language Modelscited by 1
  21. 2025Characterizing the Robustness of Black-Box LLM Planners Under Perturbed Observations with Adaptive Stress Testingcited by 1
  22. 2025Reducing Latency in LLM-Based Natural Language Commands Processing for Robot Navigationcited by 1
  23. 2025PSALM-V: Automating Symbolic Planning in Interactive Visual Environments with Large Language Modelscited by 1
  24. 2025An LLM-powered Natural-to-Robotic Language Translation Framework with Correctness Guaranteescited by 1
  25. 2025ScheduleMe: Multi-Agent Calendar Assistantcited by 1
  26. 2026On the Ability of Transformers to Verify Planscited by 1
  27. 2024Semantic Skill Grounding for Embodied Instruction-Following in Cross-Domain Environmentscited by 0
  28. 2025DataScout: Automatic Data Fact Retrieval for Statement Augmentation with an LLM-Based Agentcited by 0
  29. 2025Empowering LLMs with Parameterized Skills for Adversarial Long-Horizon Planningcited by 0
  30. 2025Code Driven Planning with Domain-Adaptive Criticcited by 0
  31. 2025Align While Search: Belief-Guided Exploratory Inference for World-Grounded Embodied Agentscited by 0
  32. 2026Neural Nonmyopic Bayesian Optimization in Dynamic Cost Settingscited by 0
  33. 2026Object Search in Partially-Known Environments via LLM-informed Model-based Planning and Prompt Selectioncited by 0
  34. 2026Multi-scale Mixture of World Models for Embodied Agents in Evolving Environmentscited by 0
  35. 2026Planning with Transformers: Chain of Computation and Structured Context Windowscited by 0
  36. 2026Terminal Symmetry as a Carrier of Asymmetric Process Knowledge: Statewise Refinement for Anytime Verified Constructioncited by 0
  37. 2026Bridging Thought and Action: Taming Long-Horizon Instability in Open-Source LLM Agents with a MetaTool-Enhanced ROS Frameworkcited by 0