IUQ: Interrogative Uncertainty Quantification for Long-Form Large Language Model Generation

arXiv:2604.15109v1 Announce Type: cross Abstract: Despite the rapid advancement of Large Language Models (LLMs), uncertainty quantification in LLM generation is a persistent challenge. Although recent approaches have achieved strong performance by restricting LLMs to produce short or constrained answer sets, many real-world applications require long-form and free-form text generation. A key difficulty in this setting is that LLMs often produce responses that are semantically coherent yet factual