14 citations · 19 across the 4 of their papers we have counts for
5 papers
Rethinking the Evaluation of LLM Fact-Checkers
Ayana Niwa, Miyu Yamada, Kouta Nakayama +3
Large language models (LLMs) are widely used to answer factual questions, but their answers can contain errors and must be fact-checked claim by claim. Yet the resulting score depe…
Human-Grounded Multimodal Benchmark with 900K-Scale Aggregated Student Response Distributions from Japan's National Assessment of Academic Ability
Kyosuke Takami, Yuka Tateisi, Satoshi Sekine +1
Authentic school examinations provide a high-validity test bed for evaluating multimodal large language models (MLLMs), yet benchmarks grounded in Japanese K-12 assessments remain…
AnswerCarefully: A Dataset for Improving the Safety of Japanese LLM Output
Hisami Suzuki, Satoru Katsumata, Takashi Kodama +3
In this paper we present AnswerCarefully, a dataset for promoting the safety and appropriateness of Japanese LLM outputs. The dataset consists of 1,800 pairs of questions and refer…
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…
Should We Respect LLMs? A Cross-Lingual Study on the Influence of Prompt Politeness on LLM Performance
Ziqi Yin, Hao Wang, Kaito Horio +2
We investigate the impact of politeness levels in prompts on the performance of large language models (LLMs). Polite language in human communications often garners more compliance…