mlsanityData to 14 Oct 2026

GPT3-to-plan: Extracting plans from text using GPT-3

arXiv 2106.07131 ↗First posted 14 Jun 2021cs.CL cs.AIcited by 26

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Abstract (arXiv)

Operations in many essential industries including finance and banking are often characterized by the need to perform repetitive sequential tasks. Despite their criticality to the business, workflows are rarely fully automated or even formally specified, though there may exist a number of natural language documents describing these procedures for the employees of the company. Plan extraction methods provide us with the possibility of extracting structure plans from such natural language descriptions of the plans/workflows, which could then be leveraged by an automated system. In this paper, we investigate the utility of generalized language models in performing such extractions directly from such texts. Such models have already been shown to be quite effective in multiple translation tasks, and our initial results seem to point to their effectiveness also in the context of plan extractions. Particularly, we show that GPT-3 is able to generate plan extraction results that are comparable to many of the current state of the art plan extraction methods.

Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). Builds on 5 of its 11 references that are in the map. First posted on arXiv 14 Jun 2021.

Builds on

5 of 11 references.

References · 5

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2016End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRFcited by 341
  3. 2015Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequencescited by 50
  4. 2016Navigational Instruction Generation as Inverse Reinforcement Learning with Neural Machine Translationcited by 12
  5. 2018Extracting Action Sequences from Texts Based on Deep Reinforcement Learningcited by 12

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Citing papers per year: 2021: 1; 2022: 6; 2023: 13; 2024: 6.

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  1. 2021AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptscited by 268
  2. 2023Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planningcited by 207
  3. 2024LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworkscited by 179
  4. 2023Translating Natural Language to Planning Goals with Large-Language Modelscited by 133
  5. 2024LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBenchcited by 94
  6. 2023Distilling Script Knowledge from Large Language Models for Constrained Language Planningcited by 45
  7. 2022Plansformer: Generating Symbolic Plans using Transformerscited by 41
  8. 2024PREGO: online mistake detection in PRocedural EGOcentric videoscited by 39
  9. 2023Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysiscited by 35
  10. 2023How to Design Translation Prompts for ChatGPT: An Empirical Studycited by 31
  11. 2023CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generationcited by 29
  12. 2022Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill Diversitycited by 22
14 more
  1. 2024Planning in Strawberry Fields: Evaluating and Improving the Planning and Scheduling Capabilities of LRM o1cited by 17
  2. 2023Exploiting Language Models as a Source of Knowledge for Cognitive Agentscited by 15
  3. 2023Towards Healthy AI: Large Language Models Need Therapists Toocited by 13
  4. 2023Transformers in Reinforcement Learning: A Surveycited by 12
  5. 2024TI-PREGO: Chain of Thought and In-Context Learning for Online Mistake Detection in PRocedural EGOcentric Videoscited by 10
  6. 2022a survey on GPT-3cited by 9
  7. 2023AE-GPT: Using Large Language Models to Extract Adverse Events from Surveillance Reports-A Use Case with Influenza Vaccine Adverse Eventscited by 8
  8. 2023Improved Instruction Ordering in Recipe-Grounded Conversationcited by 7
  9. 2022Integrating Diverse Knowledge Sources for Online One-shot Learning of Novel Taskscited by 6
  10. 2022Improving Language Model Prompting in Support of Semi-autonomous Task Learningcited by 6
  11. 2022Integrating AI Planning with Natural Language Processing: A Combination of Explicit and Tacit Knowledgecited by 3
  12. 2023Automated Action Model Acquisition from Narrative Textscited by 3
  13. 2024Enhancing Mobile "How-to" Queries with Automated Search Results Verification and Rerankingcited by 3
  14. 2023Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysiscited by 1