IC-239Implicit preference forms (choice-based and persona-driven) are significantly harder for LLMs to follow than explicit preferences at the same context length
When user preferences are revealed implicitly through a two-turn choice-based dialogue or a 4-8 turn persona-driven conversation rather than stated explicitly, all six open-source models show substantially lower preference-following accuracy even at short context lengths. For example, at ~0.2k tokens with zero-shot, Claude 3 Sonnet scores around 80% on explicit preferences but only ~41% on implicit choice-based and ~19% on implicit persona-driven. The gap persists across all models and context lengths, indicating that preference inference adds a distinct difficulty beyond long-context retrieval.
The implicit preference dialogues were constructed such that only one option adheres to the target preference, which the authors note does not guarantee 100% accurate inference from the multiple-choice selection.