While large language models (LLMs) are widely used across cultures, they often generate culturally inappropriate responses in unfamiliar cultural contexts due to biases embedded in their training data. Existing approaches primarily rely on expanding static cultural knowledge, which fails to capture the inherently rel...
Mirae Han, Harksoo Kim· Transactions of the Associat...· 0 citations
Large language models (LLMs) have shown strong performance across various tasks, but they still struggle with questions involving ethical judgment. Previous studies have attempted to train LLMs on ethical standards, but the diversity and relativity of ethical norms make them difficult to fully internalize in model para...
Flexible Self-Consistency (FSC) is proposed, which estimates problem difficulty as a continuous signal and dynamically adjusts the number of generated reasoning paths accordingly and leverages it as an indicator of model uncertainty to flexibly control the sampling budget.
Sihyeong Yeom, Geon Park, Geunyeong Jeong et al.· 0 citations
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in multimodal understanding and reasoning by integrating linguistic and visual information, while benchmarks facilitate iterative model improvement by evaluating their performance and analyzing their limitations. However, existing dialogue-based...
Seulgi Kim, Juoh Sun, Sumin Kim et al.· Proceedings of the 32nd ACM...· 0 citations
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