mlsanityData to 7 Oct 2026

MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning

arXiv 2310.16730 ↗First posted 25 Oct 2023cs.LGcited by 3

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

Abstract (arXiv)

Recently, there has been an increasing interest in automated prompt optimization based on reinforcement learning (RL). This approach offers important advantages, such as generating interpretable prompts and being compatible with black-box foundation models. However, the substantial prompt space size poses challenges for RL-based methods, often leading to suboptimal policy convergence. This paper introduces MultiPrompter, a new framework that views prompt optimization as a cooperative game between prompters which take turns composing a prompt together. Our cooperative prompt optimization effectively reduces the problem size and helps prompters learn optimal prompts. We test our method on the text-to-image task and show its ability to generate higher-quality images than baselines.

Key facts. Cited by 3 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 28 of its 37 references that are in the map. First posted on arXiv 25 Oct 2023.

Builds on

28 of 37 references.

References · 28

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
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  8. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,878
  9. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,769
  10. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
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16 more
  1. 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,519
  2. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 903
  3. 2017Counterfactual Multi-Agent Policy Gradientscited by 733
  4. 2021Learning How to Ask: Querying LMs with Mixtures of Soft Promptscited by 376
  5. 2022RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learningcited by 361
  6. 2019Emergent Tool Use From Multi-Agent Autocurriculacited by 308
  7. 2018Machine Theory of Mindcited by 222
  8. 2022Optimizing Prompts for Text-to-Image Generationcited by 204
  9. 2018Mean Field Multi-Agent Reinforcement Learningcited by 202
  10. 2017Emergent Complexity via Multi-Agent Competitioncited by 117
  11. 2018Learning to Teach in Cooperative Multiagent Reinforcement Learningcited by 45
  12. 2023Discrete Prompt Compression with Reinforcement Learningcited by 42
  13. 2020A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learningcited by 40
  14. 2023PACE: Improving Prompt with Actor-Critic Editing for Large Language Modelcited by 20
  15. 2022Influencing Long-Term Behavior in Multiagent Reinforcement Learningcited by 18
  16. 2021Context-Specific Representation Abstraction for Deep Option Learningcited by 8

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025Learning to Sample Effective and Diverse Prompts for Text-to-Image Generationcited by 16
  2. 2025Reasoning-Aware Prompt Orchestration: A Foundation Model for Multi-Agent Language Model Coordinationcited by 1
  3. 2025Creative Adversarial Testing (CAT): A Novel Framework for Evaluating Goal-Oriented Agentic AI Systemscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Prompt-Tuning Bandits: Enabling Few-Shot Generalization for Efficient Multi-Task Offline RL
  2. 2026Naive Prompt Optimization: Rethinking the Need for Complex Prompt Search
  3. 2025Prompt-R1: Collaborative Automatic Prompting Framework via End-to-end Reinforcement Learning
  4. 2025PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment
  5. 2026Environment-Grounded Automated Prompt Optimization for LLM Game Agents
  6. 2025PromptSculptor: Multi-Agent Based Text-to-Image Prompt Optimization
  7. 2022Prompting Decision Transformer for Few-Shot Policy Generalization
  8. 2026AgentGrad: Intervention-guided Prompt Optimization for Multi Agent Systems