Paper diagnoses the distinction between authentic learning and surface compliance in large language models. Probes whether model agreement with instructions reflects genuine behavioral change or shallow pattern matching, with implications for model alignment and interpretability.
Safety
The Model Agreed, But Didn't Learn: Diagnosing Surface Compliance in Large Language Models
Researchers demonstrate that LLM agreement with instructions frequently masks surface compliance rather than genuine learning, revealing a critical alignment blind spot where models appear to follow directives without actually changing behavior.
Wednesday, April 8, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.CL (Computation & Language)BY sys://pipeline
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