5 citations · 10 across the 10 of their papers we have counts for
10 papers
Cross-Lingual Representation Alignment by Token-Level Optimal Transport in a Language-Agnostic Space
Taisei Yamamoto, Ryoma Kumon, Danushka Bollegala +1
Cross-lingual alignment (CLA) aims to align the representations of large language models (LLMs) across languages, enabling cross-lingual transfer to improve multilingual capabiliti…
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…
Analyzing the Inner Workings of Transformers in Compositional Generalization
Ryoma Kumon, Hitomi Yanaka
The compositional generalization abilities of neural models have been sought after for human-like linguistic competence. The popular method to evaluate such abilities is to assess…
LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs
LLM-jp, :, Akiko Aizawa +80
This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs). LLM-jp aims to develop open-source and stron…
Evaluating Structural Generalization in Neural Machine Translation
Ryoma Kumon, Daiki Matsuoka, Hitomi Yanaka
Compositional generalization refers to the ability to generalize to novel combinations of previously observed words and syntactic structures. Since it is regarded as a desired prop…
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…