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Fine-Tuning Fixes Mode Collapse and Over-Dispersion in LLMs

This story is from 2026-09-16. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.16454v1 Announce Type: new Abstract: Recent work by Doshi and Hauser (2024), Bisbee et al. (2024), and Xie et al. (2026) raises concerns that outputs from large language models (LLMs) tend to be under-diverse: they repeat or resemble one another more often than responses from the populat…

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  1. 2026-09-16 04:00 · arXiv cs.AI
    Fine-Tuning Fixes Mode Collapse and Over-Dispersion in LLMs

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