mlsanityData to 7 Oct 2026

InterAct: Exploring the Potentials of ChatGPT as a Cooperative Agent

arXiv 2308.01552 ↗First posted 3 Aug 2023cs.AI cs.CL cs.LGcited by 16

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

This research paper delves into the integration of OpenAI's ChatGPT into embodied agent systems, evaluating its influence on interactive decision-making benchmark. Drawing a parallel to the concept of people assuming roles according to their unique strengths, we introduce InterAct. In this approach, we feed ChatGPT with varied prompts, assigning it a numerous roles like a checker and a sorter, then integrating them with the original language model. Our research shows a remarkable success rate of 98% in AlfWorld, which consists of 6 different tasks in a simulated household environment, emphasizing the significance of proficient prompt engineering. The results highlight ChatGPT's competence in comprehending and performing intricate tasks effectively in real-world settings, thus paving the way for further advancements in task planning.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 31 of its 37 references that are in the map. First posted on arXiv 3 Aug 2023.

Builds on

31 of 37 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents3 Feb

Other references · 30

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2023GPT-4 Technical Reportcited by 18,132
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  5. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  6. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  7. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  8. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,339
  9. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  10. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  11. 2021Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsitycited by 3,014
  12. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
18 more
  1. 2022Emergent Abilities of Large Language Modelscited by 2,483
  2. 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,302
  3. 2022RT-1: Robotics Transformer for Real-World Control at Scalecited by 2,007
  4. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,869
  5. 2021Decision Transformer: Reinforcement Learning via Sequence Modelingcited by 1,528
  6. 2020ALFWorld: Aligning Text and Embodied Environments for Interactive Learningcited by 1,143
  7. 2022Inner Monologue: Embodied Reasoning through Planning with Language Modelscited by 1,057
  8. 2022Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agentscited by 1,029
  9. 2021Show Your Work: Scratchpads for Intermediate Computation with Language Modelscited by 871
  10. 2019ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Taskscited by 773
  11. 2023ChatGPT for Robotics: Design Principles and Model Abilitiescited by 296
  12. 2022Multi-Game Decision Transformerscited by 212
  13. 2022Faithful Reasoning Using Large Language Modelscited by 130
  14. 2023DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agentscited by 52
  15. 2023ChatGPT Empowered Long-Step Robot Control in Various Environments: A Case Applicationcited by 48
  16. 2021Differentiable Spatial Planning using Transformerscited by 25
  17. 2023AGI for Agriculturecited by 9
  18. 2018Classification based Grasp Detection using Spatial Transformer Networkcited by 6

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Citing papers per year: 2023: 6; 2024: 7; 2025: 3.

16 papers.

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  1. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  2. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
  3. 2023Large Language Models for Robotics: A Surveycited by 132
  4. 2025Lifelong Learning of Large Language Model based Agents: A Roadmapcited by 78
  5. 2023Lyfe Agents: Generative agents for low-cost real-time social interactionscited by 49
  6. 2024m&m's: A Benchmark to Evaluate Tool-Use for multi-step multi-modal Taskscited by 38
  7. 2023An In-depth Survey of Large Language Model-based Artificial Intelligence Agentscited by 30
  8. 2024MobileAgent: enhancing mobile control via human-machine interaction and SOP integrationcited by 18
  9. 2023Towards Responsible Generative AI: A Reference Architecture for Designing Foundation Model based Agentscited by 13
  10. 2024AI Agent for Education: von Neumann Multi-Agent System Frameworkcited by 12
  11. 2024Position: Foundation Agents as the Paradigm Shift for Decision Makingcited by 9
  12. 2024A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Modelcited by 4
4 more
  1. 2024DANA: Domain-Aware Neurosymbolic Agents for Consistency and Accuracycited by 2
  2. 2025AgentArcEval: An Architecture Evaluation Method for Foundation Model based Agentscited by 2
  3. 2024Teaching Models to Improve on Tapecited by 1
  4. 2025SEQ-GPT: LLM-assisted Spatial Query via Examplecited by 0

Similar, not cited

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  1. 2025UserBench: An Interactive Gym Environment for User-Centric Agents
  2. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society
  3. 2023Exploring the Intersection of Large Language Models and Agent-Based Modeling via Prompt Engineering
  4. 2020Imitating Interactive Intelligence
  5. 2024Collaborative Gym: A Framework for Enabling and Evaluating Human-Agent Collaboration
  6. 2025A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions
  7. 2025Humanlike Multi-user Agent (HUMA): Designing a Deceptively Human AI Facilitator for Group Chats
  8. 2023Asking Before Acting: Gather Information in Embodied Decision Making with Language Models