mlsanityData to 7 Oct 2026

Hoodwinked: Deception and Cooperation in a Text-Based Game for Language Models

arXiv 2308.01404 ↗First posted 5 Jul 2023cs.CL cs.CY cs.LGcited by 46

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Abstract (arXiv)

Are current language models capable of deception and lie detection? We study this question by introducing a text-based game called textitHoodwinked, inspired by Mafia and Among Us. Players are locked in a house and must find a key to escape, but one player is tasked with killing the others. Each time a murder is committed, the surviving players have a natural language discussion then vote to banish one player from the game. We conduct experiments with agents controlled by GPT-3, GPT-3.5, and GPT-4 and find evidence of deception and lie detection capabilities. The killer often denies their crime and accuses others, leading to measurable effects on voting outcomes. More advanced models are more effective killers, outperforming smaller models in 18 of 24 pairwise comparisons. Secondary metrics provide evidence that this improvement is not mediated by different actions, but rather by stronger persuasive skills during discussions. To evaluate the ability of AI agents to deceive humans, we make this game publicly available at h https://hoodwinked.ai/ .

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). Builds on 18 of its 24 references that are in the map. First posted on arXiv 5 Jul 2023.

Builds on

18 of 24 references.

References · 18

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Emergent Abilities of Large Language Modelscited by 2,483
  3. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  4. 2023Inference-Time Intervention: Eliciting Truthful Answers from a Language Modelcited by 1,259
  5. 2022Discovering Latent Knowledge in Language Models Without Supervisioncited by 733
  6. 2023The Internal State of an LLM Knows When It's Lyingcited by 644
  7. 2018TextWorld: A Learning Environment for Text-based Gamescited by 304
  8. 2023Inverse Scaling: When Bigger Isn't Bettercited by 205
  9. 2023Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmarkcited by 174
  10. 2020Open Problems in Cooperative AIcited by 167
  11. 2023Model evaluation for extreme riskscited by 167
  12. 2019Interactive Fiction Games: A Colossal Adventurecited by 165
6 more
  1. 2021Spinning Language Models: Risks of Propaganda-As-A-Service and Countermeasurescited by 69
  2. 2021What Would Jiminy Cricket Do? Towards Agents That Behave Morallycited by 57
  3. 2023Spear Phishing With Large Language Modelscited by 49
  4. 2023Can large language models democratize access to dual-use biotechnology?cited by 33
  5. 2022Putting the Con in Context: Identifying Deceptive Actors in the Game of Mafiacited by 13
  6. 2022Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibriacited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 6; 2024: 14; 2025: 15; 2026: 11.

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  1. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
  2. 2024Frontier Models are Capable of In-context Schemingcited by 252
  3. 2023AI Deception: A Survey of Examples, Risks, and Potential Solutionscited by 185
  4. 2023Large Language Models can Strategically Deceive their Users when Put Under Pressurecited by 132
  5. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 125
  6. 2024AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathwayscited by 122
  7. 2024GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluationscited by 118
  8. 2025A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deploymentcited by 110
  9. 2023Avalon's Game of Thoughts: Battle Against Deception through Recursive Contemplationcited by 102
  10. 2024LLM as a Mastermind: A Survey of Strategic Reasoning with Large Language Modelscited by 97
  11. 2023How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questionscited by 82
  12. 2023Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arenacited by 78
34 more
  1. 2024How Far Are We on the Decision-Making of LLMs? Evaluating LLMs' Gaming Ability in Multi-Agent Environmentscited by 66
  2. 2024Uncovering Deceptive Tendencies in Language Models: A Simulated Company AI Assistantcited by 32
  3. 2024InterIntent: Investigating Social Intelligence of LLMs via Intention Understanding in an Interactive Game Contextcited by 25
  4. 2025Among Us: A Sandbox for Measuring and Detecting Agentic Deceptioncited by 24
  5. 2024AgentLens: Visual Analysis for Agent Behaviors in LLM-based Autonomous Systemscited by 23
  6. 2024Noise Injection Reveals Hidden Capabilities of Sandbagging Language Modelscited by 22
  7. 2025PropensityBench: Evaluating Latent Safety Risks in Large Language Models via an Agentic Approachcited by 19
  8. 2025Deception in LLMs: Self-Preservation and Autonomous Goals in Large Language Modelscited by 15
  9. 2024Lies, Damned Lies, and Distributional Language Statistics: Persuasion and Deception with Large Language Modelscited by 14
  10. 2024Poser: Unmasking Alignment Faking LLMs by Manipulating Their Internalscited by 13
  11. 2025WOLF: Werewolf-based Observations for LLM Deception and Falsehoodscited by 13
  12. 2024Language Models can Subtly Deceive Without Lying: A Case Study on Strategic Phrasing in Legislationcited by 10
  13. 2025When Do Large Language Models Exhibit Unsolicited Deception?cited by 9
  14. 2025Among Them: A game-based framework for assessing persuasion capabilities of LLMscited by 7
  15. 2025The Secret Agenda: LLMs Strategically Lie and Our Current Safety Tools Are Blindcited by 7
  16. 2025Evaluating & Reducing Deceptive Dialogue From Language Models with Multi-turn RLcited by 7
  17. 2024EscapeBench: Towards Advancing Creative Intelligence of Language Model Agentscited by 5
  18. 2025AI Agent Behavioral Sciencecited by 5
  19. 2024An Assessment of Model-On-Model Deceptioncited by 4
  20. 2025Do LLMs Strategically Reveal, Conceal, and Infer Information? A Theoretical and Empirical Analysis in The Chameleon Gamecited by 4
  21. 2025This Is Your Doge, If It Please You: Exploring Deception and Robustness in Mixture of LLMscited by 4
  22. 2025Ev-Trust: An Evolutionarily Stable Trust Mechanism for Decentralized LLM-Based Multi-Agent Service Economiescited by 3
  23. 2026Deception and Communication in Autonomous Multi-Agent Systems: An Experimental Study with Among Uscited by 3
  24. 2026QUACK: Questioning, Understanding, and Auditing Communicated Knowledge in Multimodal Social Deduction Agentscited by 3
  25. 2026Hidden in Plain Text: Measuring LLM Deception Quality Against Human Baselines Using Social Deduction Gamescited by 2
  26. 2026MafiaScope: Non-Invasive, Time-Resolved Belief Probing for LLM Agents in Social Deduction Gamescited by 2
  27. 2025Vibe Learning: Education in the age of AIcited by 0
  28. 2026"Dark Triad" Model Organisms of Misalignment: Narrow Fine-Tuning Mirrors Human Antisocial Behaviorcited by 0
  29. 2026SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systemscited by 0
  30. 2026Triadic Werewolf: A Jester Role for Multi-Hop Theory of Mind in LLMscited by 0
  31. 2026Understanding Large Language Modelscited by 0
  32. 2026The Politician, the Liar, and the Obedient Worker: Emerging Behavior of LLM Agents in Hierarchical Gamescited by 0
  33. 2026Lies We Can See: Joint Verbal and Non-Verbal Deception by VLM Agents in Embodied Social Interactionscited by 0
  34. 2026Detecting AI Impostors: How Do Middle Schoolers Identify LLM Agents in a Live Collaborative Setting?cited by 0