Zobrazeno 1 - 10
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pro vyhledávání: '"A. Salman"'
Autor:
Hu, Zijian, Zhang, Jipeng, Pan, Rui, Xu, Zhaozhuo, Avestimehr, Salman, He, Chaoyang, Zhang, Tong
We present Fox-1, a series of small language models (SLMs) consisting of Fox-1-1.6B and Fox-1-1.6B-Instruct-v0.1. These models are pre-trained on 3 trillion tokens of web-scraped document data and fine-tuned with 5 billion tokens of instruction-follo
Externí odkaz:
http://arxiv.org/abs/2411.05281
Autor:
Ran, Yide, Xu, Zhaozhuo, Yao, Yuhang, Hu, Zijian, Han, Shanshan, Jin, Han, Shah, Alay Dilipbhai, Zhang, Jipeng, Stripelis, Dimitris, Zhang, Tong, Avestimehr, Salman, He, Chaoyang
The rapid advancement of Large Language Models (LLMs) has led to their increased integration into mobile devices for personalized assistance, which enables LLMs to call external API functions to enhance their performance. However, challenges such as
Externí odkaz:
http://arxiv.org/abs/2411.05209
The increasing growth of social media provides us with an instant opportunity to be informed of the opinions of a large number of politically active individuals in real-time. We can get an overall idea of the ideologies of these individuals on govern
Externí odkaz:
http://arxiv.org/abs/2411.04542
The Gender Identification (GI) problem is concerned with determining the gender of the author from a given text. It has numerous applications in different fields like forensics, literature, security, marketing, trade, etc. Due to its importance, rese
Externí odkaz:
http://arxiv.org/abs/2411.04524
Autor:
Munasinghe, Shehan, Gani, Hanan, Zhu, Wenqi, Cao, Jiale, Xing, Eric, Khan, Fahad Shahbaz, Khan, Salman
Fine-grained alignment between videos and text is challenging due to complex spatial and temporal dynamics in videos. Existing video-based Large Multimodal Models (LMMs) handle basic conversations but struggle with precise pixel-level grounding in vi
Externí odkaz:
http://arxiv.org/abs/2411.04923
Artificial Intelligence (AI) research often aims to develop models that can generalize reliably across complex datasets, yet this remains challenging in fields where data is scarce, intricate, or inaccessible. This paper introduces a novel approach t
Externí odkaz:
http://arxiv.org/abs/2411.01929
Autor:
Khan, Salman, Teeti, Izzeddin, Alitappeh, Reza Javanmard, Stoian, Mihaela C., Giunchiglia, Eleonora, Singh, Gurkirt, Bradley, Andrew, Cuzzolin, Fabio
Autonomous Vehicle (AV) perception systems require more than simply seeing, via e.g., object detection or scene segmentation. They need a holistic understanding of what is happening within the scene for safe interaction with other road users. Few dat
Externí odkaz:
http://arxiv.org/abs/2411.01683
Autor:
Liu, Mira M., Saadat, Niloufar, Roth, Steven P., Niekrasz, Marek A., Giurcanu, Mihai, Shazeeb, Mohammed Salman, Carroll, Timothy J., Christoforidis, Gregory A.
This work examines the hypothesis that intravoxel incoherent motion MRI (IVIM) can quantify local cerebral blood flow (qCBF), infarct volume, and define the ischemic penumbra for determination of the perfusion-diffusion mismatch (PWI/DWI) volume in a
Externí odkaz:
http://arxiv.org/abs/2411.00671
Automated waste recycling aims to efficiently separate the recyclable objects from the waste by employing vision-based systems. However, the presence of varying shaped objects having different material types makes it a challenging problem, especially
Externí odkaz:
http://arxiv.org/abs/2410.24139
Autor:
Ibrahimzada, Ali Reza, Ke, Kaiyao, Pawagi, Mrigank, Abid, Muhammad Salman, Pan, Rangeet, Sinha, Saurabh, Jabbarvand, Reyhaneh
Code translation transforms programs from one programming language (PL) to another. Several rule-based transpilers have been designed to automate code translation between different pairs of PLs. However, the rules can become obsolete as the PLs evolv
Externí odkaz:
http://arxiv.org/abs/2410.24117