mlsanityData to 14 Oct 2026

Reflective Linguistic Programming (RLP): A Stepping Stone in Socially-Aware AGI (SocialAGI)

arXiv 2305.12647 ↗First posted 22 May 2023cs.AI cs.CL cs.HCcited by 16

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Abstract (arXiv)

This paper presents Reflective Linguistic Programming (RLP), a unique approach to conversational AI that emphasizes self-awareness and strategic planning. RLP encourages models to introspect on their own predefined personality traits, emotional responses to incoming messages, and planned strategies, enabling contextually rich, coherent, and engaging interactions. A striking illustration of RLP's potential involves a toy example, an AI persona with an adversarial orientation, a demon named `Bogus' inspired by the children's fairy tale Hansel & Gretel. Bogus exhibits sophisticated behaviors, such as strategic deception and sensitivity to user discomfort, that spontaneously arise from the model's introspection and strategic planning. These behaviors are not pre-programmed or prompted, but emerge as a result of the model's advanced cognitive modeling. The potential applications of RLP in socially-aware AGI (Social AGI) are vast, from nuanced negotiations and mental health support systems to the creation of diverse and dynamic AI personas. Our exploration of deception serves as a stepping stone towards a new frontier in AGI, one filled with opportunities for advanced cognitive modeling and the creation of truly human `digital souls'.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 8 of its 23 references that are in the map. First posted on arXiv 22 May 2023.

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8 of 23 references.

References · 8

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  4. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  5. 2023A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPTcited by 368
  6. 2023Evaluating Large Language Models in Theory of Mind Taskscited by 222
  7. 2023Reflective Artificial Intelligencecited by 4
  8. 2022Self-Aware Feedback-Based Self-Learning in Large-Scale Conversational AIcited by 3

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Citing papers per year: 2023: 2; 2024: 11; 2025: 3.

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  1. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
  2. 2024Executable Code Actions Elicit Better LLM Agentscited by 564
  3. 2024From Persona to Personalization: A Survey on Role-Playing Language Agentscited by 212
  4. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 126
  5. 2024From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agentscited by 82
  6. 2024MathVC: An LLM-Simulated Multi-Character Virtual Classroom for Mathematics Educationcited by 37
  7. 2024CI-Bench: Benchmarking Contextual Integrity of AI Assistants on Synthetic Datacited by 37
  8. 2024Exploration of LLM Multi-Agent Application Implementation Based on LangGraph+CrewAIcited by 35
  9. 2025The Future of Continual Learning in the Era of Foundation Models: Three Key Directionscited by 17
  10. 2024Causal Agent based on Large Language Modelcited by 10
  11. 2024Professional Agents -- Evolving Large Language Models into Autonomous Experts with Human-Level Competenciescited by 9
  12. 2024Concept -- An Evaluation Protocol on Conversational Recommender Systems with System-centric and User-centric Factorscited by 9
4 more
  1. 2024MARCO: Multi-Agent Real-time Chat Orchestrationcited by 5
  2. 2024Towards Goal-oriented Prompt Engineering for Large Language Models: A Surveycited by 3
  3. 2025Rethinking Group Recommender Systems in the Era of Generative AI: From One-Shot Recommendations to Agentic Group Decision Supportcited by 3
  4. 2023MindDial: Belief Dynamics Tracking with Theory-of-Mind Modeling for Situated Neural Dialogue Generationcited by 1