Reading Too Much into Context: Passive Exposure Can Steer LLM Decisions

arXiv:2609.33065 · cs.CL, cs.LG · Submitted 2026-09-27 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-09-27

Updated: 2026-09-27

Terminology

• Steering — 12× in this paper · explained in 2 episodes
• Trace — 5× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Sycophancy — 2× in this paper · explained in 4 episodes
• Thinking mode — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Adversarial Search — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 4 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• Self-Blinding and Counterfactual Self-Simulation Mitigate Biases and Sycophancy in Large Language Models
• Gemma 4 Technical Report
• Qwen3 Technical Report
• Are Language Models Sensitive to Morally Irrelevant Distractors?
• The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions
• Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Search Agents

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