Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Salman, Shaeke"'
Building on the unprecedented capabilities of large language models for command understanding and zero-shot recognition of multi-modal vision-language transformers, visual language navigation (VLN) has emerged as an effective way to address multiple
Externí odkaz:
http://arxiv.org/abs/2407.07392
Utilizing a shared embedding space, emerging multimodal models exhibit unprecedented zero-shot capabilities. However, the shared embedding space could lead to new vulnerabilities if different modalities can be misaligned. In this paper, we extend and
Externí odkaz:
http://arxiv.org/abs/2407.01157
Transformer-based models have dominated natural language processing and other areas in the last few years due to their superior (zero-shot) performance on benchmark datasets. However, these models are poorly understood due to their complexity and siz
Externí odkaz:
http://arxiv.org/abs/2402.08473
Pre-trained large foundation models play a central role in the recent surge of artificial intelligence, resulting in fine-tuned models with remarkable abilities when measured on benchmark datasets, standard exams, and applications. Due to their inher
Externí odkaz:
http://arxiv.org/abs/2401.15568
Stock price movement prediction is a challenging and essential problem in finance. While it is well established in modern behavioral finance that the share prices of related stocks often move after the release of news via reactions and overreactions
Externí odkaz:
http://arxiv.org/abs/2301.10458
Publikováno v:
GLOBECOM 2022 - 2022 IEEE Global Communications Conference
IoT device identification plays an important role in monitoring and improving the performance and security of IoT devices. Compared to traditional non-IoT devices, IoT devices provide us with both unique challenges and opportunities in detecting the
Externí odkaz:
http://arxiv.org/abs/2212.08905
Understanding the underlying mechanisms that enable the empirical successes of deep neural networks is essential for further improving their performance and explaining such networks. Towards this goal, a specific question is how to explain the "surpr
Externí odkaz:
http://arxiv.org/abs/1910.08581
Deep neural networks have achieved remarkable success in various challenging tasks. However, the black-box nature of such networks is not acceptable to critical applications, such as healthcare. In particular, the existence of adversarial examples an
Externí odkaz:
http://arxiv.org/abs/1905.05849
Autor:
Salman, Shaeke, Liu, Xiuwen
Assisted by the availability of data and high performance computing, deep learning techniques have achieved breakthroughs and surpassed human performance empirically in difficult tasks, including object recognition, speech recognition, and natural la
Externí odkaz:
http://arxiv.org/abs/1901.06566
Publikováno v:
AMIA Annu Symp Proc
Acute myocardial infarction poses significant health risks and financial burden on healthcare and families. Prediction of mortality risk among AMI patients using rich electronic health record (EHR) data can potentially save lives and healthcare costs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c04749cceec22882ef7ef887bbbf3e94
https://pubmed.ncbi.nlm.nih.gov/34457162
https://pubmed.ncbi.nlm.nih.gov/34457162
