Zobrazeno 1 - 10
of 113
pro vyhledávání: '"Md. Rizwan"'
Autor:
Md. Asad Iqbal Chowdhury, Mohammad Shamsu Uddin, Monir Ahmmed, Md. Rizwan Hassan, Mohammad Jonaed Kabir
Publikováno v:
Cogent Economics & Finance, Vol 11, Iss 1 (2023)
AbstractRecently worldwide Islamic finance has gained considerable attention. However, Islamic financial institutions face multiple risks to sustaining and growing further. Against this backdrop, the paper examines the impact of both liquidity and cr
Externí odkaz:
https://doaj.org/article/9d51720f50514646bf040b8bdf6510db
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
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:
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
Training LLMs for low-resource languages usually utilizes data augmentation from English using machine translation (MT). This, however, brings a number of challenges to LLM training: there are large costs attached to translating and curating huge amo
Externí odkaz:
http://arxiv.org/abs/2405.14277
Code synthesis, which requires a deep understanding of complex natural language problem descriptions, generation of code instructions for complex algorithms and data structures, and the successful execution of comprehensive unit tests, presents a sig
Externí odkaz:
http://arxiv.org/abs/2405.11403
Charts provide visual representations of data and are widely used for analyzing information, addressing queries, and conveying insights to others. Various chart-related downstream tasks have emerged recently, such as question-answering and summarizat
Externí odkaz:
http://arxiv.org/abs/2403.09028
Autor:
Parvez, Md Rizwan
While chain-of-thought (CoT) prompting has revolutionized how LLMs perform reasoning tasks, its current methods and variations (e.g, Self-consistency, ReACT, Reflexion, Tree-of-Thoughts (ToT), Cumulative Reasoning (CR)) suffer from limitations like s
Externí odkaz:
http://arxiv.org/abs/2401.05787
Autor:
Sadat, Mobashir, Zhou, Zhengyu, Lange, Lukas, Araki, Jun, Gundroo, Arsalan, Wang, Bingqing, Menon, Rakesh R, Parvez, Md Rizwan, Feng, Zhe
Hallucination is a well-known phenomenon in text generated by large language models (LLMs). The existence of hallucinatory responses is found in almost all application scenarios e.g., summarization, question-answering (QA) etc. For applications requi
Externí odkaz:
http://arxiv.org/abs/2312.05200