Zobrazeno 1 - 10
of 22 751
pro vyhledávání: '"PARVEZ, A. A."'
Video Highlight Detection and Moment Retrieval (HD/MR) are essential in video analysis. Recent joint prediction transformer models often overlook their cross-task dynamics and video-text alignment and refinement. Moreover, most models typically use l
Externí odkaz:
http://arxiv.org/abs/2412.01558
Mathematical reasoning has proven to be a critical yet challenging task for large language models (LLMs), as they often struggle with complex multi-step problems. To address these limitations, we introduce the Monte Carlo Nash Equilibrium Self-Refine
Externí odkaz:
http://arxiv.org/abs/2411.15645
The growing volume of biomedical scholarly document abstracts presents an increasing challenge in efficiently retrieving accurate and relevant information. To address this, we introduce a novel approach that integrates an optimized topic modelling fr
Externí odkaz:
http://arxiv.org/abs/2411.00041
Autor:
Ali, Parvez, Baby, Annmaria, Xavier, D. Antony, Varghese, Eddith Sarah, A., Theertha Nair, Ali, Haidar
The modern era always looks into advancements in technology. Design and topology of interconnection networks play a mutual role in development of technology. Analysing the topological properties and characteristics of an interconnection network is no
Externí odkaz:
http://arxiv.org/abs/2411.04135
Autor:
Ali, Parvez, Baby, Annmaria, Xavier, D. Antony, A, Theertha Nair, Ali, Haidar, Kirmani, Syed Ajaz K.
For a graph $\mathbb{Q}=(\mathbb{V},\mathbb{E})$, the transformation graphs are defined as graphs with vertex set being $\mathbb{V(Q)} \cup \mathbb{E(Q)}$ and edge set is described following certain conditions. In comparison to the structure descript
Externí odkaz:
http://arxiv.org/abs/2410.09122
In a hyperconnected environment, medical institutions are particularly concerned with data privacy when sharing and transmitting sensitive patient information due to the risk of data breaches, where malicious actors could intercept sensitive informat
Externí odkaz:
http://arxiv.org/abs/2410.07900
Autor:
Islam, Shayekh Bin, Rahman, Md Asib, Hossain, K S M Tozammel, Hoque, Enamul, Joty, Shafiq, Parvez, Md Rizwan
Retrieval-Augmented Generation (RAG) has been shown to enhance the factual accuracy of Large Language Models (LLMs), but existing methods often suffer from limited reasoning capabilities in effectively using the retrieved evidence, particularly when
Externí odkaz:
http://arxiv.org/abs/2410.01782
Autor:
Islam, Mohammed Saidul, Laskar, Md Tahmid Rahman, Parvez, Md Rizwan, Hoque, Enamul, Joty, Shafiq
Data-driven storytelling is a powerful method for conveying insights by combining narrative techniques with visualizations and text. These stories integrate visual aids, such as highlighted bars and lines in charts, along with textual annotations exp
Externí odkaz:
http://arxiv.org/abs/2408.05346
Autor:
Gosal, Gurpreet, Xu, Yishi, Ramakrishnan, Gokul, Joshi, Rituraj, Sheinin, Avraham, Zhiming, Chen, Mishra, Biswajit, Vassilieva, Natalia, Hestness, Joel, Sengupta, Neha, Sahu, Sunil Kumar, Jia, Bokang, Pandit, Onkar, Katipomu, Satheesh, Kamboj, Samta, Ghosh, Samujjwal, Pal, Rahul, Mullah, Parvez, Doraiswamy, Soundar, Chami, Mohamed El Karim, Nakov, Preslav
We present an efficient method for adapting a monolingual Large Language Model (LLM) to another language, addressing challenges of catastrophic forgetting and tokenizer limitations. We focus this study on adapting Llama 2 to Arabic. Our two-stage app
Externí odkaz:
http://arxiv.org/abs/2407.12869
Autor:
Laskar, Md Tahmid Rahman, Alqahtani, Sawsan, Bari, M Saiful, Rahman, Mizanur, Khan, Mohammad Abdullah Matin, Khan, Haidar, Jahan, Israt, Bhuiyan, Amran, Tan, Chee Wei, Parvez, Md Rizwan, Hoque, Enamul, Joty, Shafiq, Huang, Jimmy
Large Language Models (LLMs) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough evaluation of these models is crucial before deploying them in real-w
Externí odkaz:
http://arxiv.org/abs/2407.04069