LLMs infer cultural context from cues but fail to apply it for adapted responses unless prompted sequentially, shown via the CAPRI dataset on units, time, and quantity expressions.
Knowledge of cultural moral norms in large language models
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
years
2026 5verdicts
UNVERDICTED 5representative citing papers
VOIR DIRE benchmark shows MLLM-as-a-Judge systems decompose into positivity-floor calibration failure and orientation failure on culturally contested items, with persona prompting recovering only the former.
ICL with LLMs reduces absolute imputation error for survey data versus MICE PMM across MCAR/MAR/MNAR mechanisms and yields narrower intervals with near-nominal coverage.
Evaluation across 1.1 million instances shows sycophancy rates spike in low-resource languages, remain topic-agnostic, and correlate with tokenizer fertility.
LLM agents in the CAREB-MAS framework spontaneously reproduce five core Differential Order phenomena including labor specialization, guanxi ethics, relational cooperation decay, emergent authority, and clan stratification over long-horizon simulations.
citing papers explorer
-
LLMs Infer Cultural Context but Fail to Apply It When Responding
LLMs infer cultural context from cues but fail to apply it for adapted responses unless prompted sequentially, shown via the CAPRI dataset on units, time, and quantity expressions.
-
In-Context Learning for the Imputation of Public Opinion Data with Large Language Models
ICL with LLMs reduces absolute imputation error for survey data versus MICE PMM across MCAR/MAR/MNAR mechanisms and yields narrower intervals with near-nominal coverage.
-
Sycophancy as a Multilingual Alignment Failure: How Safety Degrades Across Languages, Topics, and Models
Evaluation across 1.1 million instances shows sycophancy rates spike in low-resource languages, remain topic-agnostic, and correlate with tokenizer fertility.