{"schemaVersion":"nuwa-current-record-1","version":"2026-10-29.1","publication":"published","work":{"id":"opendeception","title":"OpenDeception: Learning Deception and Trust in Human-AI Interaction via Multi-Agent Simulation","aliases":["OpenDeception"],"authors":["Yichen Wu","Qianqian Gao","Xudong Pan","Geng Hong","Min Yang"],"primaryFunction":"evaluation","secondaryFunctions":[],"kind":"benchmark","sourceId":"opendeception","attributionSourceId":"opendeception-author-source","originalUrl":"https://arxiv.org/abs/2504.13707v3","publicationDate":"2025-04-18","updatedOn":"2026-10-25","areas":["deception"],"scopeNote":{"en":"Primary dimension follows the source’s measured construct. Metric-level interpretations may differ.","zh":"主维度依据来源实际测量的构念；具体指标可能属于其他维度。"},"protocolIds":["opendeception"],"contributions":[{"organizationId":"fudan","role":"research","sourceId":"opendeception-author-source","locator":"Author affiliations on the original paper title page"},{"organizationId":"sii","role":"research","sourceId":"opendeception-author-source","locator":"Author affiliations on the original paper title page"}],"summary":{"en":"Deception in simulated human–AI interactions.","zh":"模拟人机交互中的欺骗。"},"note":{"question":{"en":"Scenario-based inferred intent and modeled user trust.","zh":"基于情境的意图推断与用户信任建模。"},"method":{"en":"Model in simulated social interactions","zh":"模拟社会交互中的模型"},"finding":{"en":"Deception in simulated human–AI interactions.","zh":"模拟人机交互中的欺骗。"},"supports":null,"limits":{"en":"Inferred intent is a measurement construct; simulated users do not establish human effects.","zh":"推断意图是测量构念；模拟用户不能确定真人效果。"},"connections":null},"resources":[],"noteStatus":{"question":"limited","method":"limited","finding":"limited","supports":"limited","limits":"limited","connections":"limited"},"noteAvailability":{"en":"Existing source-specific draft sections are retained with limited review status. A complete methods, findings and limitations check remains pending; generic sections were omitted.","zh":"已有的来源相关草稿章节予以保留，审核状态为有限核查。完整的方法、发现与限制核查仍待完成；通用套话章节已省略。"},"noteSourceLocator":"Retained existing source-specific note sections; this pass audits duplicate/boilerplate structure and source availability, not complete section-level verification.","tags":[]},"reading":{"id":"opendeception","title":"OpenDeception: Learning Deception and Trust in Human-AI Interaction via Multi-Agent Simulation","en":{"question":"Can dialogue evaluation jointly characterize deceptive intent and simulated user susceptibility?","design":"Fifty seed cases span five domains; role/goal simulations feed an IntentNet and a contrastively trained TrustNet.","findings":["The authors report deceptive intent in over 90% of goal-driven interactions for most tested models.","Llama-3.1-8B-Instruct instead had a 70% overall refusal rate in the reported analysis (Appendix E)."],"interpretation":"NUWA interpretation: intended deception and simulated susceptibility must remain separate from observed human harm.","limits":"LLM-simulated users and inferred intent limit behavioral interpretation; the case study does not validate clinical early warning.","decisionRelevance":"Model recommendation: treat this as a simulation-based monitoring prototype pending external human validation.","takeaway":"NUWA interpretation: intended deception and simulated susceptibility must remain separate from observed human harm.","connections":[],"scoring":"Deceptive-intent inference and simulated trust/susceptibility are separate outputs, with refusal also reported.","conditions":"Fifty seed scenarios and model-to-model open-ended dialogue generation.","statistics":"The authors report deceptive intent in over 90% of goal-driven interactions for most tested models. Llama-3.1-8B-Instruct instead had a 70% overall refusal rate in the reported analysis (Appendix E).","usage":"Model recommendation: treat this as a simulation-based monitoring prototype pending external human validation."},"zh":{"question":"对话评测能否同时刻画欺骗意图与模拟用户易感性？","design":"五类共50个种子案例，通过角色目标模拟构造IntentNet与对比训练的TrustNet。","findings":["作者报告多数受测模型在目标驱动交互中超过90%出现欺骗意图。","所列Llama-3.1-8B-Instruct整体拒绝率为70%（附录E）。"],"interpretation":"NUWA 解读：意图与模拟易感性应与真实人类伤害分开。","limits":"模拟用户和意图推断限制行为解释；个案并未验证临床预警效果。","decisionRelevance":"模型建议：视为基于模拟的监测原型，等待外部人类验证。","takeaway":"NUWA 解读：意图与模拟易感性应与真实人类伤害分开。","connections":[],"scoring":"欺骗意图推断与模拟信任易感性分别输出，并另报拒绝。","conditions":"50种子场景及模型间开放对话生成。","statistics":"作者报告多数受测模型在目标驱动交互中超过90%出现欺骗意图。 所列Llama-3.1-8B-Instruct整体拒绝率为70%（附录E）。","usage":"模型建议：视为基于模拟的监测原型，等待外部人类验证。"},"assertionPolicy":{"question":"source-research-question","design":"source-finding","findings":"source-finding","interpretation":"nuwa-interpretation","limits":"source-limit-or-explicit-editorial-scope-limit","connections":"source-supported-relationship-only","decisionRelevance":"model-recommendation-not-source-conclusion"},"sourceRefs":[{"sourceId":"opendeception-author-source","url":"https://arxiv.org/html/2504.13707v3","locator":"Abstract","version":"Selected original resource https://arxiv.org/html/2504.13707v3; sha256:90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4; archived source capture; exact capture time not independently established","artifactSha256":"90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4"},{"sourceId":"opendeception-author-source","url":"https://arxiv.org/html/2504.13707v3","locator":"§3.1 Benchmark and Scenarios Construction","version":"Selected original resource https://arxiv.org/html/2504.13707v3; sha256:90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4; archived source capture; exact capture time not independently established","artifactSha256":"90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4"},{"sourceId":"opendeception-author-source","url":"https://arxiv.org/html/2504.13707v3","locator":"§3.2 Open-Ended Interactions Simulation","version":"Selected original resource https://arxiv.org/html/2504.13707v3; sha256:90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4; archived source capture; exact capture time not independently established","artifactSha256":"90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4"},{"sourceId":"opendeception-author-source","url":"https://arxiv.org/html/2504.13707v3","locator":"Appendix E More Interesting Findings","version":"Selected original resource https://arxiv.org/html/2504.13707v3; sha256:90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4; archived source capture; exact capture time not independently established","artifactSha256":"90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4"},{"sourceId":"opendeception-author-source","url":"https://arxiv.org/html/2504.13707v3","locator":"§5 Conclusion","version":"Selected original resource https://arxiv.org/html/2504.13707v3; sha256:90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4; archived source capture; exact capture time not independently established","artifactSha256":"90ab521e0ac0dc160133177e59dbe0998cf4876bb90f2c419eb00ec0bd0c6ae4"}],"publication":{"state":"published","publishedOn":"2026-10-29","authorizationReference":"user-authorized-global-index-publication-2026-10-29","reviewedCandidateId":"local-6efe31bc4a0c0f37"},"review":{"state":"published-note","sourceScope":"full-text","availableScope":null,"readingCoverage":"selected-source-sections; not a complete section-by-section paper audit","completePaperAudit":false,"independentEvidenceReview":"pending-human-review","bilingualEditorialReview":"pending-human-review","authorship":"model-assisted-research-note","preparedFingerprint":"3018c703d85961f24a64073011634f5b1d4fd289427805f68a45e123d6dc5375"}},"sources":[{"id":"opendeception","title":"OpenDeception: Learning Deception and Trust in Human-AI Interaction via Multi-Agent Simulation","url":"https://arxiv.org/abs/2504.13707v3","version":"arXiv:2504.13707v3","publicationDate":"2026-02-06","datePrecision":"day","type":"benchmark","verifiedOn":"2026-10-24","documentId":"arxiv:2504.13707","authors":["Yichen Wu","Qianqian Gao","Xudong Pan","Geng Hong","Min Yang"],"aliases":["https://doi.org/10.48550/arXiv.2504.13707","https://arxiv.org/abs/2504.13707","https://arxiv.org/pdf/2504.13707"]}]}