DIAL: Steerable Language Models with Distilled Instruction-Adherence Levels
When a user says "Keep it short", how short should the LLM's response be? More generally, users and applications require different levels of instruction adherence, but prompting does not reliably provide fine-grained control over them. We therefore study "steerable language models" that provide fine-grained numerical control over the degree to which models follow general instructions specified in text. However, existing approaches do not jointly offer fine-grained control, efficiency, and scalability across diverse instructions. To address this gap, we introduce DIAL (Distilled Instruction-Adherence Levels) to achieve all three properties. For fine-grained control, we perform classifier-f...
| Authors | Thanh Q. Tran, John Russell Himawan, Arun Verma et al. |
|---|---|
| Primary category | cs.AI |
| Published | 22 October 2026 |
| Last updated at source | 22 October 2026 |
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