Zobrazeno 1 - 10
of 37 532
pro vyhledávání: '"Cam, A."'
Bundle recommendation aims to suggest a set of interconnected items to users. However, diverse interaction types and sparse interaction matrices often pose challenges for previous approaches in accurately predicting user-bundle adoptions. Inspired by
Externí odkaz:
http://arxiv.org/abs/2412.18092
The objective of multimodal intent recognition (MIR) is to leverage various modalities-such as text, video, and audio-to detect user intentions, which is crucial for understanding human language and context in dialogue systems. Despite advances in th
Externí odkaz:
http://arxiv.org/abs/2412.08529
Comparative reviews are pivotal in understanding consumer preferences and influencing purchasing decisions. Comparative Quintuple Extraction (COQE) aims to identify five key components in text: the target entity, compared entities, compared aspects,
Externí odkaz:
http://arxiv.org/abs/2412.08508
Multimodal Aspect-Based Sentiment Analysis (MABSA) combines text and images to perform sentiment analysis but often struggles with irrelevant or misleading visual information. Existing methodologies typically address either sentence-image denoising o
Externí odkaz:
http://arxiv.org/abs/2412.08489
Autor:
Chen, Panpan, Park, Seonyeong, Cam, Refik Mert, Huang, Hsuan-Kai, Oraevsky, Alexander A., Villa, Umberto, Anastasio, Mark A.
In certain three-dimensional (3D) applications of photoacoustic computed tomography (PACT), including \textit{in vivo} breast imaging, hemispherical measurement apertures that enclose the object within their convex hull are employed for data acquisit
Externí odkaz:
http://arxiv.org/abs/2412.01971
Autor:
McLeman, Cam, Rasmussen, Christopher
Motivated by a long-standing question of Ihara, we investigate heavenly abelian varieties -- abelian varieties defined over a number field $K$ that exhibit constrained $\ell$-adic Galois representations at some rational prime $\ell$. We demonstrate a
Externí odkaz:
http://arxiv.org/abs/2410.18389
Autor:
Wang, Zhibin, Li, Shipeng, Zhou, Yuhang, Li, Xue, Gu, Rong, Cam-Tu, Nguyen, Tian, Chen, Zhong, Sheng
Large language models (LLMs) have achieved remarkable performance and are widely deployed in various applications, while the serving of LLM inference has raised concerns about user experience and serving throughput. Accordingly, service level objecti
Externí odkaz:
http://arxiv.org/abs/2410.14257
Autor:
Ding, Chuanghao, Liu, Xuejing, Tang, Wei, Li, Juan, Wang, Xiaoliang, Zhao, Rui, Nguyen, Cam-Tu, Tan, Fei
This paper introduces SynthDoc, a novel synthetic document generation pipeline designed to enhance Visual Document Understanding (VDU) by generating high-quality, diverse datasets that include text, images, tables, and charts. Addressing the challeng
Externí odkaz:
http://arxiv.org/abs/2408.14764
Multimodal Emotion Recognition in Conversations (ERC) is a typical multimodal learning task in exploiting various data modalities concurrently. Prior studies on effective multimodal ERC encounter challenges in addressing modality imbalances and optim
Externí odkaz:
http://arxiv.org/abs/2408.12895
In Couette flow, the liquid atoms adjacent to a solid substrate may have a finite average tangential velocity relative to the substrate. This so-called slip has been frequently observed. However, the particular molecular-level mechanisms that give ri
Externí odkaz:
http://arxiv.org/abs/2409.04445