Zobrazeno 1 - 10
of 475
pro vyhledávání: '"Kobayashi, Ichiro"'
Professionals' decisions are the focus of every field. For example, politicians' decisions will influence the future of the country, and stock analysts' decisions will impact the market. Recognizing the influential role of professionals' perspectives
Externí odkaz:
http://arxiv.org/abs/2410.07225
The advancement of text generation models has granted us the capability to produce coherent and convincing text on demand. Yet, in real-life circumstances, individuals do not continuously generate text or voice their opinions. For instance, consumers
Externí odkaz:
http://arxiv.org/abs/2410.01169
This paper explores designing artificial organizations with professional behavior in investments using a multi-agent simulation. The method mimics hierarchical decision-making in investment firms, using news articles to inform decisions. A large-scal
Externí odkaz:
http://arxiv.org/abs/2410.00354
This paper investigates the role of expert-designed hint in enhancing sentiment analysis on financial social media posts. We explore the capability of large language models (LLMs) to empathize with writer perspectives and analyze sentiments. Our find
Externí odkaz:
http://arxiv.org/abs/2409.17448
Autor:
Chen, Chung-Chi, Huang, Hen-Hsen, Chen, Hsin-Hsi, Takamura, Hiroya, Kobayashi, Ichiro, Miyao, Yusuke
In the era of rapid Internet and social media platform development, individuals readily share their viewpoints online. The overwhelming quantity of these posts renders comprehensive analysis impractical. This necessitates an efficient recommendation
Externí odkaz:
http://arxiv.org/abs/2409.17417
Thinking about the future is one of the important activities that people do in daily life. Futurists also pay a lot of effort into figuring out possible scenarios for the future. We argue that the exploration of this direction is still in an early st
Externí odkaz:
http://arxiv.org/abs/2405.20708
Autor:
Virgo, Felix, Cheng, Fei, Pereira, Lis Kanashiro, Asahara, Masayuki, Kobayashi, Ichiro, Kurohashi, Sadao
We propose a voting-driven semi-supervised approach to automatically acquire the typical duration of an event and use it as pseudo-labeled data. The human evaluation demonstrates that our pseudo labels exhibit surprisingly high accuracy and balanced
Externí odkaz:
http://arxiv.org/abs/2403.18504
Temporal relation classification is a pair-wise task for identifying the relation of a temporal link (TLINK) between two mentions, i.e. event, time, and document creation time (DCT). It leads to two crucial limits: 1) Two TLINKs involving a common me
Externí odkaz:
http://arxiv.org/abs/2310.20236
Autor:
Shimomoto, Erica K., Marrese-Taylor, Edison, Takamura, Hiroya, Kobayashi, Ichiro, Nakayama, Hideki, Miyao, Yusuke
This paper explores the task of Temporal Video Grounding (TVG) where, given an untrimmed video and a natural language sentence query, the goal is to recognize and determine temporal boundaries of action instances in the video described by the query.
Externí odkaz:
http://arxiv.org/abs/2209.13359
Publikováno v:
SemEval 2022-Task 2
We propose a multilingual adversarial training model for determining whether a sentence contains an idiomatic expression. Given that a key challenge with this task is the limited size of annotated data, our model relies on pre-trained contextual repr
Externí odkaz:
http://arxiv.org/abs/2206.03025