Zobrazeno 1 - 10
of 241 949
pro vyhledávání: '"A, Gan"'
Knowledge distillation is a mainstream algorithm in model compression by transferring knowledge from the larger model (teacher) to the smaller model (student) to improve the performance of student. Despite many efforts, existing methods mainly invest
Externí odkaz:
http://arxiv.org/abs/2410.14143
Autor:
Yang, Yuzhe, Zhang, Yifei, Hu, Yan, Guo, Yilin, Gan, Ruoli, He, Yueru, Lei, Mingcong, Zhang, Xiao, Wang, Haining, Xie, Qianqian, Huang, Jimin, Yu, Honghai, Wang, Benyou
This paper introduces the UCFE: User-Centric Financial Expertise benchmark, an innovative framework designed to evaluate the ability of large language models (LLMs) to handle complex real-world financial tasks. UCFE benchmark adopts a hybrid approach
Externí odkaz:
http://arxiv.org/abs/2410.14059
Autor:
Atobe, Hiraku, Gan, Wee Teck, Ichino, Atsushi, Kaletha, Tasho, Mínguez, Alberto, Shin, Sug Woo
The local intertwining relation is an identity that gives precise information about the action of normalized intertwining operators on parabolically induced representations. We prove several instances of the local intertwining relation for quasi-spli
Externí odkaz:
http://arxiv.org/abs/2410.13504
In recent years, mobile phone data has been widely used for human mobility analytics. Identifying individual activity locations is the fundamental step for mobile phone data processing. Current methods typically aggregate spatially adjacent location
Externí odkaz:
http://arxiv.org/abs/2410.13912
Autor:
Meng, Chunlei, Yang, Jiacheng, Lin, Wei, Liu, Bowen, Zhang, Hongda, ouyang, chun, Gan, Zhongxue
Convolutional neural networks (CNNs) and vision transformers (ViTs) have become essential in computer vision for local and global feature extraction. However, aggregating these architectures in existing methods often results in inefficiencies. To add
Externí odkaz:
http://arxiv.org/abs/2410.11428
Non-suicidal self-injury (NSSI) is a serious threat to the physical and mental health of adolescents, significantly increasing the risk of suicide and attracting widespread public concern. Electroencephalography (EEG), as an objective tool for identi
Externí odkaz:
http://arxiv.org/abs/2410.12159
We address the challenge of causal discovery in structural equation models with additive noise without imposing additional assumptions on the underlying data-generating process. We introduce local search in additive noise model (LoSAM), which general
Externí odkaz:
http://arxiv.org/abs/2410.11759
In an era marked by robust technological growth and swift information renewal, furnishing researchers and the populace with top-tier, avant-garde academic insights spanning various domains has become an urgent necessity. The KDD Cup 2024 AQA Challeng
Externí odkaz:
http://arxiv.org/abs/2410.10455
Crafting effective features is a crucial yet labor-intensive and domain-specific task within machine learning pipelines. Fortunately, recent advancements in Large Language Models (LLMs) have shown promise in automating various data science tasks, inc
Externí odkaz:
http://arxiv.org/abs/2410.12865
Autor:
Gan, Chengguang, Mori, Tatsunori
The Mutual Reinforcement Effect (MRE) investigates the synergistic relationship between word-level and text-level classifications in text classification tasks. It posits that the performance of both classification levels can be mutually enhanced. How
Externí odkaz:
http://arxiv.org/abs/2410.09745