Zobrazeno 1 - 10
of 1 050
pro vyhledávání: '"Tetsuya SAKAI"'
Autor:
Haoxiang Shi, Tetsuya Sakai
Publikováno v:
IEEE Access, Vol 12, Pp 43734-43746 (2024)
Pre-trained language models are the cornerstone of modern natural language processing and information retrieval. However, fine-tuning all the parameters reduces the efficiency of models both in training and inference owing to their increasingly heavy
Externí odkaz:
https://doaj.org/article/2204231175cb4a8d982a5ffed312c364
Publikováno v:
IEEE Access, Vol 12, Pp 420-434 (2024)
In the field of multimodal understanding and generation, tackling inherent uncertainties is essential for mitigating ambiguous interpretations across multiple targets. We introduce the Probability Distribution Encoder (PDE), a versatile, plug-and-pla
Externí odkaz:
https://doaj.org/article/9d0638419d3c4a7c8072bb0541a678d1
This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Infor
Publikováno v:
IEEE Access, Vol 11, Pp 142829-142845 (2023)
Zero-shot learning is an approach where models generalize to unseen tasks without direct training on them. We introduce the Unified Multiple-Choice (UniMC) framework, which is format-independent, compatible with various formats, and applicable to tas
Externí odkaz:
https://doaj.org/article/ce984123f4a54ae0b1cf0b75c5096aaf
Autor:
Haoxiang Shi, Tetsuya Sakai
Publikováno v:
IEEE Access, Vol 11, Pp 84134-84143 (2023)
Contrastive learning is a promising approach to unsupervised learning, as it inherits the advantages of well-studied deep models without a dedicated and complex model design. In this paper, based on bidirectional encoder representations from transfor
Externí odkaz:
https://doaj.org/article/81e700f5a315419480e39cfe19355455
Autor:
Saori Murata, Morio Nakamura, Kai Sugihara, Tetsuya Sakai, Kota Ishioka, Saeko Takahashi, Shinji Sasada, Hiroyuki Yasuda, Koichi Fukunaga
Publikováno v:
Asian Pacific Journal of Cancer Care, Vol 7, Iss 1, Pp 191-196 (2022)
Background: The neutrophil-to-lymphocyte ratio (NLR) is recognized as a predictive and prognostic biomarker in various malignancies. We investigated the utility of the NLR in patients with advanced non-small cell lung cancer (NSCLC) in the early phas
Externí odkaz:
https://doaj.org/article/4fbc4265c5c3490795df4aa8dbe218c2
Autor:
Tohru Nishimura, Chisakou Fuse, Masayuki Akita, Nobuhisa Takase, Eri Maeda, Koichiro Abe, Akihito Kozuki, Kunio Yokoyama, Tomohiro Tanaka, Shinji Kishi, Toshihiko Sakamoto, Tetsuya Sakai, Kunihiko Kaneda
Publikováno v:
Surgical Case Reports, Vol 7, Iss 1, Pp 1-6 (2021)
Abstract Background Gastrobronchial fistulas are rare, but life-threatening, complications of esophagectomy. They are caused by anastomotic leakage and mainly occur around anastomotic sites. In the present paper, we report a rare case of leakage from
Externí odkaz:
https://doaj.org/article/591de7922c5d4fdda73b9c58791593c8
Publikováno v:
ACM Transactions on Information Systems; Jan2024, Vol. 42 Issue 1, p1-31, 31p
Autor:
ROITERO, KEVIN, LA BARBERA, DAVID, SOPRANO, MICHAEL, DEMARTINI, GIANLUCA, MIZZARO, STEFANO, TETSUYA SAKAI
Publikováno v:
ACM Transactions on Information Systems; Jan2024, Vol. 42 Issue 1, p1-26, 26p
Publikováno v:
ACM Transactions on Information Systems; Jan2024, Vol. 42 Issue 1, p1-36, 36p