Zobrazeno 1 - 10
of 291
pro vyhledávání: '"Yoshinaga, Naoki"'
Language models often struggle with handling factual knowledge, exhibiting factual hallucination issue. This makes it vital to evaluate the models' ability to recall its parametric knowledge about facts. In this study, we introduce a knowledge probin
Externí odkaz:
http://arxiv.org/abs/2406.12277
Acquiring factual knowledge for language models (LMs) in low-resource languages poses a serious challenge, thus resorting to cross-lingual transfer in multilingual LMs (ML-LMs). In this study, we ask how ML-LMs acquire and represent factual knowledge
Externí odkaz:
http://arxiv.org/abs/2403.05189
Open-domain dialogue systems have started to engage in continuous conversations with humans. Those dialogue systems are required to be adjusted to the human interlocutor and evaluated in terms of their perspective. However, it is questionable whether
Externí odkaz:
http://arxiv.org/abs/2401.02256
Autor:
Wang, Yueguan, Yoshinaga, Naoki
Despite the prevalence of pretrained language models in natural language understanding tasks, understanding lengthy text such as document is still challenging due to the data sparseness problem. Inspired by that humans develop their ability of unders
Externí odkaz:
http://arxiv.org/abs/2312.00513
The meanings of words and phrases depend not only on where they are used (contexts) but also on who use them (writers). Pretrained language models (PLMs) are powerful tools for capturing context, but they are typically pretrained and fine-tuned for u
Externí odkaz:
http://arxiv.org/abs/2309.07727
Product attribute-value identification (PAVI) has been studied to link products on e-commerce sites with their attribute values (e.g., ) using product text as clues. Technical demands from real-world e-commerce platforms require PAV
Externí odkaz:
http://arxiv.org/abs/2306.05605
Autor:
Yoshinaga, Naoki
Accurate neural models are much less efficient than non-neural models and are useless for processing billions of social media posts or handling user queries in real time with a limited budget. This study revisits the fastest pattern-based NLP methods
Externí odkaz:
http://arxiv.org/abs/2305.19045
Autor:
Wang, Zihan, Yoshinaga, Naoki
Esports, a sports competition on video games, has become one of the most important sporting events. Although esports play logs have been accumulated, only a small portion of them accompany text commentaries for the audience to retrieve and understand
Externí odkaz:
http://arxiv.org/abs/2212.10935
Although named entity recognition (NER) helps us to extract domain-specific entities from text (e.g., artists in the music domain), it is costly to create a large amount of training data or a structured knowledge base to perform accurate NER in the t
Externí odkaz:
http://arxiv.org/abs/2210.07523
We make decisions by reacting to changes in the real world, in particular, the emergence and disappearance of impermanent entities such as events, restaurants, and services. Because we want to avoid missing out on opportunities or making fruitless ac
Externí odkaz:
http://arxiv.org/abs/2210.07404