Search Results for author: Shintaro Ozaki

Found 6 papers, 1 papers with code

Understanding the Impact of Confidence in Retrieval Augmented Generation: A Case Study in the Medical Domain

no code implementations29 Dec 2024 Shintaro Ozaki, Yuta Kato, Siyuan Feng, Masayo Tomita, Kazuki Hayashi, Ryoma Obara, Masafumi Oyamada, Katsuhiko Hayashi, Hidetaka Kamigaito, Taro Watanabe

Retrieval Augmented Generation (RAG) complements the knowledge of Large Language Models (LLMs) by leveraging external information to enhance response accuracy for queries.

RAG

BQA: Body Language Question Answering Dataset for Video Large Language Models

no code implementations17 Oct 2024 Shintaro Ozaki, Kazuki Hayashi, Miyu Oba, Yusuke Sakai, Hidetaka Kamigaito, Taro Watanabe

To address this, we propose a dataset, BQA, a body language question answering dataset, to validate whether the model can correctly interpret emotions from short clips of body language comprising 26 emotion labels of videos of body language.

Question Answering

Towards Cross-Lingual Explanation of Artwork in Large-scale Vision Language Models

no code implementations3 Sep 2024 Shintaro Ozaki, Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito, Katsuhiko Hayashi, Taro Watanabe

As the performance of Large-scale Vision Language Models (LVLMs) improves, they are increasingly capable of responding in multiple languages, and there is an expectation that the demand for explanations generated by LVLMs will grow.

Machine Translation Translation

An Implementation of Werewolf Agent That does not Truly Trust LLMs

no code implementations3 Sep 2024 Takehiro Sato, Shintaro Ozaki, Daisaku Yokoyama

Werewolf is an incomplete information game, which has several challenges when creating a computer agent as a player given the lack of understanding of the situation and individuality of utterance (e. g., computer agents are not capable of characterful utterance or situational lying).

Language Modeling Language Modelling +1

LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs

no code implementations4 Jul 2024 LLM-jp, :, Akiko Aizawa, Eiji Aramaki, Bowen Chen, Fei Cheng, Hiroyuki Deguchi, Rintaro Enomoto, Kazuki Fujii, Kensuke Fukumoto, Takuya Fukushima, Namgi Han, Yuto Harada, Chikara Hashimoto, Tatsuya Hiraoka, Shohei Hisada, Sosuke Hosokawa, Lu Jie, Keisuke Kamata, Teruhito Kanazawa, Hiroki Kanezashi, Hiroshi Kataoka, Satoru Katsumata, Daisuke Kawahara, Seiya Kawano, Atsushi Keyaki, Keisuke Kiryu, Hirokazu Kiyomaru, Takashi Kodama, Takahiro Kubo, Yohei Kuga, Ryoma Kumon, Shuhei Kurita, Sadao Kurohashi, Conglong Li, Taiki Maekawa, Hiroshi Matsuda, Yusuke Miyao, Kentaro Mizuki, Sakae Mizuki, Yugo Murawaki, Akim Mousterou, Ryo Nakamura, Taishi Nakamura, Kouta Nakayama, Tomoka Nakazato, Takuro Niitsuma, Jiro Nishitoba, Yusuke Oda, Hayato Ogawa, Takumi Okamoto, Naoaki Okazaki, Yohei Oseki, Shintaro Ozaki, Koki Ryu, Rafal Rzepka, Keisuke Sakaguchi, Shota Sasaki, Satoshi Sekine, Kohei Suda, Saku Sugawara, Issa Sugiura, Hiroaki Sugiyama, Hisami Suzuki, Jun Suzuki, Toyotaro Suzumura, Kensuke Tachibana, Yu Takagi, Kyosuke Takami, Koichi Takeda, Masashi Takeshita, Masahiro Tanaka, Kenjiro Taura, Arseny Tolmachev, Nobuhiro Ueda, Zhen Wan, Shuntaro Yada, Sakiko Yahata, Yuya Yamamoto, Yusuke Yamauchi, Hitomi Yanaka, Rio Yokota, Koichiro Yoshino

This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs).

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