Best AI News โ€” Updated Every 3 Hours
Story Page
← All Stories
Home Papers Story
Papers

Sampling More, Getting Less: Calibration is the Diversity Bottleneck in LLMs

Via ArXiv cs.CL
Wednesday, May 13, 2026 ยท 4:00AM
Summary

arXiv:2605.11128v1 Announce Type: new Abstract: Diversity is essential for language-model applications ranging from creative generation to scientific discovery, yet modern LLMs often collapse into a narrow subset of plausible outputs. While prior work has developed benchmarks for measuring this lack

Continue reading the full article
Read at ArXiv cs.CL
arxiv.org
Back to all stories