Papers with Batch Generation
Large Language Models Are Bad Dice Players: LLMs Struggle to Generate Random Numbers from Statistical Distributions (2026.acl-long)
Copied to clipboard
| Challenge: | Existing large language models lack a functional internal sampler to faithfully sample from specified probability distributions . lack of robust sampling mechanisms across diverse application scenarios is a critical functional requirement . |
| Approach: | They propose to use a dual-protocol design to disentangle failure modes . batch generation achieves only modest statistical validity, while independent requests collapse almost entirely . |
| Outcome: | The proposed model fails to enforce uniform answer-position constraints and violates demographic targets in attribute-constrained text-to-image prompt synthesis. |