Zobrazeno 1 - 10
of 967
pro vyhledávání: '"SAKAI, Yusuke"'
Autor:
Sasaoka, Seiya, Sakai, Yusuke, Dominguez, Diego, Somiya, Kentaro, Sakai, Kazuki, Oohara, Ken-ichi, Meyer-Conde, Marco, Takahashi, Hirotaka
Publikováno v:
PhysRevD.110.104020,2024
Core-collapse supernovae (CCSNe) are potential multimessenger events detectable by current and future gravitational wave (GW) detectors. The GW signals emitted during these events are expected to provide insights into the explosion mechanism and the
Externí odkaz:
http://arxiv.org/abs/2411.08407
Publikováno v:
The Astrophysical Journal, Volume 974, Number 2, 245 (2024)
Decadal changes in a nearby supernova remnant (SNR) were analyzed using a multiepoch maximum likelihood estimation (MLE) approach. To achieve greater accuracy in capturing the dynamics of SNRs, kinematic features and point-spread function effects wer
Externí odkaz:
http://arxiv.org/abs/2410.15072
Text generation commonly relies on greedy and beam decoding that limit the search space and degrade output quality. Minimum Bayes Risk (MBR) decoding can mitigate this problem by utilizing automatic evaluation metrics and model-generated pseudo-refer
Externí odkaz:
http://arxiv.org/abs/2410.15021
Autor:
Ozaki, Shintaro, Hayashi, Kazuki, Oba, Miyu, Sakai, Yusuke, Kamigaito, Hidetaka, Watanabe, Taro
A large part of human communication relies on nonverbal cues such as facial expressions, eye contact, and body language. Unlike language or sign language, such nonverbal communication lacks formal rules, requiring complex reasoning based on commonsen
Externí odkaz:
http://arxiv.org/abs/2410.13206
Autor:
Ozaki, Shintaro, Hayashi, Kazuki, Sakai, Yusuke, Kamigaito, Hidetaka, Hayashi, Katsuhiko, Watanabe, Taro
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. However, pre-trai
Externí odkaz:
http://arxiv.org/abs/2409.01584
The natural language understanding (NLU) performance of large language models (LLMs) has been evaluated across various tasks and datasets. The existing evaluation methods, however, do not take into account the variance in scores due to differences in
Externí odkaz:
http://arxiv.org/abs/2408.12263
Autor:
Ide, Yusuke, Nishida, Yuto, Oba, Miyu, Sakai, Yusuke, Vasselli, Justin, Kamigaito, Hidetaka, Watanabe, Taro
The grammatical knowledge of language models (LMs) is often measured using a benchmark of linguistic minimal pairs, where LMs are presented with a pair of acceptable and unacceptable sentences and required to judge which is acceptable. The existing d
Externí odkaz:
http://arxiv.org/abs/2408.09639
With the increase in the more fluent ad texts automatically created by natural language generation technology, it is in the high demand to verify the quality of these creatives in a real-world setting. We propose AdTEC, the first public benchmark to
Externí odkaz:
http://arxiv.org/abs/2408.05906
Minimum Bayes risk (MBR) decoding is a decision rule of text generation tasks that outperforms conventional maximum a posterior (MAP) decoding using beam search by selecting high-quality outputs based on a utility function rather than those with high
Externí odkaz:
http://arxiv.org/abs/2408.04167
It is very challenging to curate a dataset for language-specific knowledge and common sense in order to evaluate natural language understanding capabilities of language models. Due to the limitation in the availability of annotators, most current mul
Externí odkaz:
http://arxiv.org/abs/2406.04215