Zobrazeno 1 - 10
of 8 424
pro vyhledávání: '"Miyao, A."'
The lack of data transparency in Large Language Models (LLMs) has highlighted the importance of Membership Inference Attack (MIA), which differentiates trained (member) and untrained (non-member) data. Though it shows success in previous studies, rec
Externí odkaz:
http://arxiv.org/abs/2412.13475
Natural language is commonly used to describe instrument timbre, such as a "warm" or "heavy" sound. As these descriptors are based on human perception, there can be disagreement over which acoustic features correspond to a given adjective. In this wo
Externí odkaz:
http://arxiv.org/abs/2412.11769
We consider an infinitely extended system of fermions on a $d$-dimensional lattice with (magnetic) translation-invariant short-range interactions. We further assume that the system has a unique gapped ground state. Physically, this is a model for the
Externí odkaz:
http://arxiv.org/abs/2411.06967
Unsupervised constituency parsers organize phrases within a sentence into a tree-shaped syntactic constituent structure that reflects the organization of sentence semantics. However, the traditional objective of maximizing sentence log-likelihood (LL
Externí odkaz:
http://arxiv.org/abs/2410.02558
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
We propose a reinforcement learning-based search strategy to explore new physics beyond the Standard Model. The reinforcement learning, which is one of machine learning methods, is a powerful approach to find model parameters with phenomenological co
Externí odkaz:
http://arxiv.org/abs/2409.10023