Malleable Prompting: Turning Natural Language Preferences into Interactive Widgets for LLM Control

Jul 15, 2026

Researchers introduce Malleable Prompting, a technique that transforms natural language preference expressions into interactive GUI widgets such as sliders and toggles for controlling large language model (LLM) outputs. The method includes a new decoding algorithm that adjusts token probabilities based on widget settings. A user study demonstrates that this approach enables users to achieve target preferences more precisely and perceive greater controllability and transparency compared to standard natural language prompting.

Why it matters: This work presents a novel, interactive approach that could make controlling LLM outputs more intuitive and effective for users.

Full story at: arXiv Computation and Language ↗