Zobrazeno 1 - 10
of 35 578
pro vyhledávání: '"Peipei, An"'
In recent years, text classification methods based on neural networks and pre-trained models have gained increasing attention and demonstrated excellent performance. However, these methods still have some limitations in practical applications: (1) Th
Externí odkaz:
http://arxiv.org/abs/2412.09922
Autor:
Liu, Xuannan, Cui, Xing, Li, Peipei, Li, Zekun, Huang, Huaibo, Xia, Shuhan, Zhang, Miaoxuan, Zou, Yueying, He, Ran
The rapid evolution of multimodal foundation models has led to significant advancements in cross-modal understanding and generation across diverse modalities, including text, images, audio, and video. However, these models remain susceptible to jailb
Externí odkaz:
http://arxiv.org/abs/2411.09259
In recent years, bundle recommendation systems have gained significant attention in both academia and industry due to their ability to enhance user experience and increase sales by recommending a set of items as a bundle rather than individual items.
Externí odkaz:
http://arxiv.org/abs/2411.00341
This paper investigates whether the hexagonal structure of grid cells provides any performance benefits or if it merely represents a biologically convenient configuration. Utilizing the Vector-HaSH content addressable memory model as a model of the g
Externí odkaz:
http://arxiv.org/abs/2410.11886
Generalized additive models (GAM) have been successfully applied to high dimensional data analysis. However, most existing methods cannot simultaneously estimate the link function, the component functions and the variable interaction. To alleviate th
Externí odkaz:
http://arxiv.org/abs/2410.06012
Multi-label data stream usually contains noisy labels in the real-world applications, namely occuring in both relevant and irrelevant labels. However, existing online multi-label classification methods are mostly limited in terms of label quality and
Externí odkaz:
http://arxiv.org/abs/2410.02394
Autor:
Zhou, Sheng, Xiao, Junbin, Yang, Xun, Song, Peipei, Guo, Dan, Yao, Angela, Wang, Meng, Chua, Tat-Seng
Existing efforts in text-based video question answering (TextVideoQA) are criticized for their opaque decisionmaking and heavy reliance on scene-text recognition. In this paper, we propose to study Grounded TextVideoQA by forcing models to answer que
Externí odkaz:
http://arxiv.org/abs/2409.14319
Currently, the rapid development of computer vision and deep learning has enabled the creation or manipulation of high-fidelity facial images and videos via deep generative approaches. This technology, also known as deepfake, has achieved dramatic pr
Externí odkaz:
http://arxiv.org/abs/2409.14289
In this work, we propose and analyze two two-level hybrid Schwarz preconditioners for solving the Helmholtz equation with high wave number in two and three dimensions. Both preconditioners are defined over a set of overlapping subdomains, with each p
Externí odkaz:
http://arxiv.org/abs/2408.07669
Document-level relation extraction (DocRE) aims to extract relations between entities from unstructured document text. Compared to sentence-level relation extraction, it requires more complex semantic understanding from a broader text context. Curren
Externí odkaz:
http://arxiv.org/abs/2407.21384