Copertina

LH-Deception: Simulating and Understanding LLM Deceptive Behaviors in Long-Horizon Interactions

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Xu, Yang, Zhang, Xuanming, Yeh, Samuel, Dhamala, Jwala, Dia, Ousmane, Gupta, Rahul, Li, Sharon
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

DECOR: Auditing LLM Deception via Information Manipulation Theory
di: Cai, Linyue, et al.
Pubblicazione: (2026)

OpenDeception: Learning Deception and Trust in Human-AI Interaction via Multi-Agent Simulation
di: Wu, Yichen, et al.
Pubblicazione: (2025)

Cognition-of-Thought Elicits Social-Aligned Reasoning in Large Language Models
di: Zhang, Xuanming, et al.
Pubblicazione: (2025)

MetaMind: Modeling Human Social Thoughts with Metacognitive Multi-Agent Systems
di: Zhang, Xuanming, et al.
Pubblicazione: (2025)

DeceptGuard :A Constitutional Oversight Framework For Detecting Deception in LLM Agents
di: Mukhopadhyay, Snehasis
Pubblicazione: (2026)

DeceptionBench: A Comprehensive Benchmark for AI Deception Behaviors in Real-world Scenarios
di: Huang, Yao, et al.
Pubblicazione: (2025)

Deceptive Patterns of Intelligent and Interactive Writing Assistants
di: Benharrak, Karim, et al.
Pubblicazione: (2024)

Can Deception Detection Go Deeper? Dataset, Evaluation, and Benchmark for Deception Reasoning
di: Chen, Kang, et al.
Pubblicazione: (2024)

The Facade of Truth: Uncovering and Mitigating LLM Susceptibility to Deceptive Evidence
di: Wan, Herun, et al.
Pubblicazione: (2026)

Clean First, Align Later: Benchmarking Preference Data Cleaning for Reliable LLM Alignment
di: Yeh, Samuel, et al.
Pubblicazione: (2025)

Tokenization Matters: Navigating Data-Scarce Tokenization for Gender Inclusive Language Technologies
di: Ovalle, Anaelia, et al.
Pubblicazione: (2023)

Can Factual Statements be Deceptive? The DeFaBel Corpus of Belief-based Deception
di: Velutharambath, Aswathy, et al.
Pubblicazione: (2024)

D-REX: A Benchmark for Detecting Deceptive Reasoning in Large Language Models
di: Krishna, Satyapriya, et al.
Pubblicazione: (2025)

Do Large Language Models Exhibit Spontaneous Rational Deception?
di: Taylor, Samuel M., et al.
Pubblicazione: (2025)

Probing the Limits of the Lie Detector Approach to LLM Deception
di: Berger, Tom-Felix
Pubblicazione: (2026)

What if Deception Cannot be Detected? A Cross-Linguistic Study on the Limits of Deception Detection from Text
di: Velutharambath, Aswathy, et al.
Pubblicazione: (2025)

How Entangled is Factuality and Deception in German?
di: Velutharambath, Aswathy, et al.
Pubblicazione: (2024)

An Assessment of Model-On-Model Deception
di: Heitkoetter, Julius, et al.
Pubblicazione: (2024)

How Retrieved Context Shapes Internal Representations in RAG
di: Yeh, Samuel, et al.
Pubblicazione: (2026)

Dynamic Emotion and Personality Profiling for Multimodal Deception Detection
di: Zheng, Li, et al.
Pubblicazione: (2026)

PU-Lie: Lightweight Deception Detection in Imbalanced Diplomatic Dialogues via Positive-Unlabeled Learning
di: Kuwar, Bhavinkumar Vinodbhai, et al.
Pubblicazione: (2025)

AgentShield: Deception-based Compromise Detection for Tool-using LLM Agents
di: Rassul, Yassin H., et al.
Pubblicazione: (2026)

SEPSIS: I Can Catch Your Lies -- A New Paradigm for Deception Detection
di: Rani, Anku, et al.
Pubblicazione: (2023)

Lying to Win: Assessing LLM Deception through Human-AI Games and Parallel-World Probing
di: Marioriyad, Arash, et al.
Pubblicazione: (2026)

To Tell The Truth: Language of Deception and Language Models
di: Hazra, Sanchaita, et al.
Pubblicazione: (2023)

SafetyNet: Detecting Harmful Outputs in LLMs by Modeling and Monitoring Deceptive Behaviors
di: Chaudhary, Maheep, et al.
Pubblicazione: (2025)

How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts
di: Qian, Yusu, et al.
Pubblicazione: (2024)

CONSCIENTIA: Can LLM Agents Learn to Strategize? Emergent Deception and Trust in a Multi-Agent NYC Simulation
di: Sinha, Aarush, et al.
Pubblicazione: (2026)

Pressure-Testing Deception Probes in LLMs: Scaling, Robustness, and the Geometry of Deceptive Representations
di: Kumar, Sachin
Pubblicazione: (2026)

Uncovering Deceptive Tendencies in Language Models: A Simulated Company AI Assistant
di: Järviniemi, Olli, et al.
Pubblicazione: (2024)

Semantic Deception: When Reasoning Models Can't Compute an Addition
di: de Leeuw, Nathaniël, et al.
Pubblicazione: (2025)

Can MLLMs Read the Room? A Multimodal Benchmark for Assessing Deception in Multi-Party Social Interactions
di: Kang, Caixin, et al.
Pubblicazione: (2025)

Dharma, Data and Deception: An LLM-Powered Rhetorical Analysis of Cow-Urine Health Claims on YouTube
di: Munir, Sheza, et al.
Pubblicazione: (2026)

LUMINA: Detecting Hallucinations in RAG System with Context-Knowledge Signals
di: Yeh, Samuel, et al.
Pubblicazione: (2025)

Human vs. Machine Deception: Distinguishing AI-Generated and Human-Written Fake News Using Ensemble Learning
di: Jaeger, Samuel, et al.
Pubblicazione: (2026)

MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviews
di: Ignat, Oana, et al.
Pubblicazione: (2024)

Deception Abilities Emerged in Large Language Models
di: Hagendorff, Thilo
Pubblicazione: (2023)

SPADE-Bench: Evaluating Spontaneous Strategic Deception in Agents via Plan-Action Divergence
di: Bu, Yuyan, et al.
Pubblicazione: (2026)

Voting-based Multimodal Automatic Deception Detection
di: Touma, Lana, et al.
Pubblicazione: (2023)

Revealing the Deceptiveness of Knowledge Editing: A Mechanistic Analysis of Superficial Editing
di: Xie, Jiakuan, et al.
Pubblicazione: (2025)