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pro vyhledávání: '"Ushiku"'
In materials science, finding crystal structures that have targeted properties is crucial. While recent methodologies such as Bayesian optimization and deep generative models have made some advances on this issue, these methods often face difficultie
Externí odkaz:
http://arxiv.org/abs/2410.08562
A college-level benchmark dataset for large language models (LLMs) in the materials science field, MaterialBENCH, is constructed. This dataset consists of problem-answer pairs, based on university textbooks. There are two types of problems: one is th
Externí odkaz:
http://arxiv.org/abs/2409.03161
Autor:
Maeda, Koki, Hirasawa, Tosho, Hashimoto, Atsushi, Harashima, Jun, Rybicki, Leszek, Fukasawa, Yusuke, Ushiku, Yoshitaka
Procedural video understanding is gaining attention in the vision and language community. Deep learning-based video analysis requires extensive data. Consequently, existing works often use web videos as training resources, making it challenging to qu
Externí odkaz:
http://arxiv.org/abs/2408.02272
Autor:
Ushikubo, Fernanda Yumi
Publikováno v:
Repositório Institucional da UnicampUniversidade Estadual de CampinasUNICAMP.
Orientador: Kuiz Antonio Viotto
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos
Made available in DSpace on 2018-08-05T22:26:46Z (GMT). No. of bitstreams: 1 Ushikubo_FernandaYumi_M.pdf: 197
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos
Made available in DSpace on 2018-08-05T22:26:46Z (GMT). No. of bitstreams: 1 Ushikubo_FernandaYumi_M.pdf: 197
Externí odkaz:
http://repositorio.unicamp.br/jspui/handle/REPOSIP/254650
Scientific posters are used to present the contributions of scientific papers effectively in a graphical format. However, creating a well-designed poster that efficiently summarizes the core of a paper is both labor-intensive and time-consuming. A sy
Externí odkaz:
http://arxiv.org/abs/2407.19787
Visual question answering aims to provide responses to natural language questions given visual input. Recently, visual programmatic models (VPMs), which generate executable programs to answer questions through large language models (LLMs), have attra
Externí odkaz:
http://arxiv.org/abs/2407.19410
Autor:
Taniai, Tatsunori, Igarashi, Ryo, Suzuki, Yuta, Chiba, Naoya, Saito, Kotaro, Ushiku, Yoshitaka, Ono, Kanta
Predicting physical properties of materials from their crystal structures is a fundamental problem in materials science. In peripheral areas such as the prediction of molecular properties, fully connected attention networks have been shown to be succ
Externí odkaz:
http://arxiv.org/abs/2403.11686
This paper presents a Tri-branch Neural Fusion (TNF) approach designed for classifying multimodal medical images and tabular data. It also introduces two solutions to address the challenge of label inconsistency in multimodal classification. Traditio
Externí odkaz:
http://arxiv.org/abs/2403.01802
Large language models require updates to remain up-to-date or adapt to new domains by fine-tuning them with new documents. One key is memorizing the latest information in a way that the memorized information is extractable with a query prompt. Howeve
Externí odkaz:
http://arxiv.org/abs/2402.12170
Autor:
Lalande, Florian, Matsubara, Yoshitomo, Chiba, Naoya, Taniai, Tatsunori, Igarashi, Ryo, Ushiku, Yoshitaka
Symbolic Regression (SR) searches for mathematical expressions which best describe numerical datasets. This allows to circumvent interpretation issues inherent to artificial neural networks, but SR algorithms are often computationally expensive. This
Externí odkaz:
http://arxiv.org/abs/2312.04070