Bridging Natural Language and Interactive What-If Interfaces via LLM-Generated Declarative Specifications
What-if analysis (WIA) lets users explore hypothetical scenarios by adjusting parameters, applying constraints, and scoping data through interactive interfaces. Current tools fall short: spreadsheet and BI tools require laborious setup, while LLM-generated interfaces frequently misinterpret analytical intent. It remains unclear whether an explicit intermediate representation is needed, or whether LLMs can generate WIA interfaces directly. We build a benchmark of 405 WIA questions across 11 types and 5 datasets with human-authored ground-truth intent, and find that direct one-shot generation across three LLMs fails to produce a working interface in 17-45% of cases and, when interfaces rend...
| Authors | Sneha Gathani, Sirui Zeng, Diya Patel et al. |
|---|---|
| Primary category | cs.AI |
| Published | 8 April 2026 |
| Last updated at source | 6 October 2026 |
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