LLM agents' motivations are predictable, but belief systems remain opaque

Researchers have conducted a large-scale experiment using Llama-3.1-8B agents to understand how much an agent's motivations and belief systems can be inferred from its behavior. The study found a significant asymmetry, with motivations being highly predictable (98-100% accuracy) while belief systems proved much harder to discern, even for advanced transformer models which reached only 34.0% accuracy. This difficulty in inferring belief systems, particularly for neutral alignments, suggests limitations in what can be understood about an LLM agent's values solely from its observable actions. AI

IMPACT Highlights limitations in inferring LLM agent values, impacting alignment research and agent interpretability.

RANK_REASON Academic paper detailing a controlled experiment on LLM agent behavior. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

• Jason Starace
• Llama-3.1:8b
• long short-term memory
• transformers

• paper
• model release

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