8 papers
Analysis of the Neglect-Zero Effect in Large Language Models
Jin Tanaka, Daiki Matsuoka, Ryoma Kumon +1
We investigate the extent to which the language processing of LLMs resembles human cognitive processes, focusing on a human cognitive bias called the …
Fine-Grained Analysis of Shared Syntactic Mechanisms in Language Models
Ryoma Kumon, Hitomi Yanaka
While language models demonstrate sophisticated syntactic capabilities, the extent to which their internal mechanisms align with cross-constructional principles studied in linguist…
Neuron-Level Analysis of Cultural Understanding in Large Language Models
Taisei Yamamoto, Ryoma Kumon, Danushka Bollegala +1
As large language models (LLMs) are increasingly deployed worldwide, ensuring their fair and comprehensive cultural understanding is important. However, LLMs exhibit cultural bias…
Bias Mitigation or Cultural Commonsense? Evaluating LLMs with a Japanese Dataset
Taisei Yamamoto, Ryoma Kumon, Danushka Bollegala +1
Large language models (LLMs) exhibit social biases, prompting the development of various debiasing methods. However, debiasing methods may degrade the capabilities of LLMs. Previou…
Intersectional Bias in Japanese Large Language Models from a Contextualized Perspective
Hitomi Yanaka, Xinqi He, Jie Lu +6
An increasing number of studies have examined the social bias of rapidly developed large language models (LLMs). Although most of these studies have focused on bias occurring in a…
JBBQ: Japanese Bias Benchmark for Analyzing Social Biases in Large Language Models
Hitomi Yanaka, Namgi Han, Ryoma Kumon +5
With the development of large language models (LLMs), social biases in these LLMs have become a pressing issue. Although there are various benchmarks for social biases across langu…