Unknown Unknowns: Do Hidden Intentions in LLMs Evade Detection?

arXiv:2601.18552 · cs.CL, cs.LG · Submitted 2026-01-26 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-01-26

Updated: 2026-08-31

Terminology

• Accuracy — 22× in this paper · explained in 1 episode
• LLM judge — 14× in this paper · explained in 2 episodes
• Grounding — 10× in this paper · explained in 3 episodes
• Sycophancy — 10× in this paper · explained in 4 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Benchmarking — 6× in this paper · explained in 3 episodes
• False Positive Rate — 5× in this paper
• Generative AI — 5× in this paper · explained in 2 episodes
• Steering — 4× in this paper · explained in 2 episodes
• Accountability — 3× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Annotator Agreement — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Prompt Engineering — 3× in this paper · explained in 4 episodes
• Actor — 2× in this paper · explained in 3 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• False Negative Rate — 2× in this paper
• Hallucination — 2× in this paper · explained in 3 episodes
• Human-in-the-Loop — 2× in this paper · explained in 3 episodes
• Regret — 2× in this paper · explained in 3 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Agentic Workflows — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Cognitive Load — 1× in this paper · explained in 2 episodes
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Nadia — 1× in this paper · explained in 2 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Vector Representations — 1× in this paper · explained in 2 episodes

Sources

• Taxonomizing Representational Harms using Speech Act Theory
• Rethinking the Evaluation of Secure Code Generation
• Bias and Fairness in Large Language Models: A Survey
• Improving alignment of dialogue agents via targeted human judgements
• TruthEval: A Dataset to Evaluate LLM Truthfulness and Reliability
• Evaluating Large Language Models with Psychometrics
• TRUTH DECAY: Quantifying Multi-Turn Sycophancy in Language Models
• Auditing language models for hidden objectives
• Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction
• Measuring Stereotype and Deviation Biases in Large Language Models
• Benchmarking Gender and Political Bias in Large Language Models
• The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships

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