Simple supervision improves LLM distributional alignment with diverse population groups on three datasets, with evaluation across multiple models and prompts providing a benchmark.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CL 2verdicts
UNVERDICTED 2representative citing papers
LLMs exhibit persistent inertia in value orientations, with harm avoidance and fairness remaining skewed across persona prompts.
citing papers explorer
-
Improving the Distributional Alignment of LLMs using Supervision
Simple supervision improves LLM distributional alignment with diverse population groups on three datasets, with evaluation across multiple models and prompts providing a benchmark.
-
Inertia in Moral and Value Judgments of Large Language Models
LLMs exhibit persistent inertia in value orientations, with harm avoidance and fairness remaining skewed across persona prompts.