Zobrazeno 1 - 10
of 6 082
pro vyhledávání: '"Suzumura A"'
Large Language Models are applied to recommendation tasks such as items to buy and news articles to read. Point of Interest is quite a new area to sequential recommendation based on language representations of multimodal datasets. As a first step to
Externí odkaz:
http://arxiv.org/abs/2410.03265
Autor:
Chen, Junyi, Suzumura, Toyotaro
In recent years, Recommender Systems (RS) have witnessed a transformative shift with the advent of Large Language Models (LLMs) in the field of Natural Language Processing (NLP). Models such as GPT-3.5/4, Llama, have demonstrated unprecedented capabi
Externí odkaz:
http://arxiv.org/abs/2409.16674
Autor:
Hanai, Masatoshi, Ishikawa, Ryo, Kawamura, Mitsuaki, Ohnishi, Masato, Takenaka, Norio, Nakamura, Kou, Matsumura, Daiju, Fujikawa, Seiji, Sakamoto, Hiroki, Ochiai, Yukinori, Okane, Tetsuo, Kuroki, Shin-Ichiro, Yamada, Atsuo, Suzumura, Toyotaro, Shiomi, Junichiro, Taura, Kenjiro, Mita, Yoshio, Shibata, Naoya, Ikuhara, Yuichi
In modern materials science, effective and high-volume data management across leading-edge experimental facilities and world-class supercomputers is indispensable for cutting-edge research. However, existing integrated systems that handle data from t
Externí odkaz:
http://arxiv.org/abs/2409.06734
In news recommendation systems, reducing popularity bias is essential for delivering accurate and diverse recommendations. This paper presents POPK, a new method that uses temporal-counterfactual analysis to mitigate the influence of popular news art
Externí odkaz:
http://arxiv.org/abs/2407.09939
In recent years, journalists have expressed concerns about the increasing trend of news article avoidance, especially within specific domains. This issue has been exacerbated by the rise of recommender systems. Our research indicates that recommender
Externí odkaz:
http://arxiv.org/abs/2407.09137
Autor:
LLM-jp, Aizawa, Akiko, Aramaki, Eiji, Chen, Bowen, Cheng, Fei, Deguchi, Hiroyuki, Enomoto, Rintaro, Fujii, Kazuki, Fukumoto, Kensuke, Fukushima, Takuya, Han, Namgi, Harada, Yuto, Hashimoto, Chikara, Hiraoka, Tatsuya, Hisada, Shohei, Hosokawa, Sosuke, Jie, Lu, Kamata, Keisuke, Kanazawa, Teruhito, Kanezashi, Hiroki, Kataoka, Hiroshi, Katsumata, Satoru, Kawahara, Daisuke, Kawano, Seiya, Keyaki, Atsushi, Kiryu, Keisuke, Kiyomaru, Hirokazu, Kodama, Takashi, Kubo, Takahiro, Kuga, Yohei, Kumon, Ryoma, Kurita, Shuhei, Kurohashi, Sadao, Li, Conglong, Maekawa, Taiki, Matsuda, Hiroshi, Miyao, Yusuke, Mizuki, Kentaro, Mizuki, Sakae, Murawaki, Yugo, Nakamura, Ryo, Nakamura, Taishi, Nakayama, Kouta, Nakazato, Tomoka, Niitsuma, Takuro, Nishitoba, Jiro, Oda, Yusuke, Ogawa, Hayato, Okamoto, Takumi, Okazaki, Naoaki, Oseki, Yohei, Ozaki, Shintaro, Ryu, Koki, Rzepka, Rafal, Sakaguchi, Keisuke, Sasaki, Shota, Sekine, Satoshi, Suda, Kohei, Sugawara, Saku, Sugiura, Issa, Sugiyama, Hiroaki, Suzuki, Hisami, Suzuki, Jun, Suzumura, Toyotaro, Tachibana, Kensuke, Takagi, Yu, Takami, Kyosuke, Takeda, Koichi, Takeshita, Masashi, Tanaka, Masahiro, Taura, Kenjiro, Tolmachev, Arseny, Ueda, Nobuhiro, Wan, Zhen, Yada, Shuntaro, Yahata, Sakiko, Yamamoto, Yuya, Yamauchi, Yusuke, Yanaka, Hitomi, Yokota, Rio, Yoshino, Koichiro
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 strong Japanese LLMs, and as of this writing, more than 1,500 participants
Externí odkaz:
http://arxiv.org/abs/2407.03963
Large language models (LLMs) have recently transformed natural language processing, enabling machines to generate human-like text and engage in meaningful conversations. This development necessitates speed, efficiency, and accessibility in LLM infere
Externí odkaz:
http://arxiv.org/abs/2406.08413
Publikováno v:
J. Phys. Soc. Jpn. 93, 054704 (2024)
The Seebeck coefficient is examined for two-dimensional Dirac electrons in the three-quarter filled organic conductor alpha-(BEDT-TTF)_2I_3 under hydrostatic pressure, where the Seebeck coefficient is proportional to the ratio of the thermoelectric c
Externí odkaz:
http://arxiv.org/abs/2404.05914
We present the Evolving Graph Fourier Transform (EFT), the first invertible spectral transform that captures evolving representations on temporal graphs. We motivate our work by the inadequacy of existing methods for capturing the evolving graph spec
Externí odkaz:
http://arxiv.org/abs/2402.16078
Autor:
Misra, Gaurav, Suzumura, Akihiro, Campo, Andres Rodriguez, Chenna, Kautilya, Bailey, Sean, Drinkard, John
In this letter, an integrated task planning and reactive motion planning framework termed Multi-FLEX is presented that targets real-world, industrial multi-robot applications. Reactive motion planning has been attractive for the purposes of collision
Externí odkaz:
http://arxiv.org/abs/2401.17214