Zobrazeno 1 - 10
of 1 897
pro vyhledávání: '"Amin, Mohammad A"'
Autor:
Samin, Md. Nazmus Sadat, Ahad, Jawad Ibn, Medha, Tanjila Ahmed, Rahman, Fuad, Amin, Mohammad Ruhul, Mohammed, Nabeel, Rahman, Shafin
This study focuses on recognizing Bangladeshi dialects and converting diverse Bengali accents into standardized formal Bengali speech. Dialects, often referred to as regional languages, are distinctive variations of a language spoken in a particular
Externí odkaz:
http://arxiv.org/abs/2411.10879
Autor:
Ahad, Jawad Ibn, Sultan, Rafeed Mohammad, Kaikobad, Abraham, Rahman, Fuad, Amin, Mohammad Ruhul, Mohammed, Nabeel, Rahman, Shafin
This study investigates the automation of meta-analysis in scientific documents using large language models (LLMs). Meta-analysis is a robust statistical method that synthesizes the findings of multiple studies support articles to provide a comprehen
Externí odkaz:
http://arxiv.org/abs/2411.10878
Autor:
Islam, Md Touhidul, Sojib, Noushad, Kabir, Imran, Amit, Ashiqur Rahman, Amin, Mohammad Ruhul, Billah, Syed Masum
Navigating multi-level menus with complex hierarchies remains a big challenge for blind and low-vision users, who predominantly use screen readers to interact with computers. To that end, we demonstrate Wheeler, a three-wheeled input device with two
Externí odkaz:
http://arxiv.org/abs/2408.13173
Autor:
Islam, Md Touhidul, Sojib, Noushad, Kabir, Imran, Amit, Ashiqur Rahman, Amin, Mohammad Ruhul, Billah, Syed Masum
Blind users rely on keyboards and assistive technologies like screen readers to interact with user interface (UI) elements. In modern applications with complex UI hierarchies, navigating to different UI elements poses a significant accessibility chal
Externí odkaz:
http://arxiv.org/abs/2408.13166
Autor:
Kabir, Muhammad Rafsan, Sultan, Rafeed Mohammad, Asif, Ihsanul Haque, Ahad, Jawad Ibn, Rahman, Fuad, Amin, Mohammad Ruhul, Mohammed, Nabeel, Rahman, Shafin
Aligning large language models (LLMs) with a human reasoning approach ensures that LLMs produce morally correct and human-like decisions. Ethical concerns are raised because current models are prone to generating false positives and providing malicio
Externí odkaz:
http://arxiv.org/abs/2408.11879
Autor:
King, Andrew D., Nocera, Alberto, Rams, Marek M., Dziarmaga, Jacek, Wiersema, Roeland, Bernoudy, William, Raymond, Jack, Kaushal, Nitin, Heinsdorf, Niclas, Harris, Richard, Boothby, Kelly, Altomare, Fabio, Berkley, Andrew J., Boschnak, Martin, Chern, Kevin, Christiani, Holly, Cibere, Samantha, Connor, Jake, Dehn, Martin H., Deshpande, Rahul, Ejtemaee, Sara, Farré, Pau, Hamer, Kelsey, Hoskinson, Emile, Huang, Shuiyuan, Johnson, Mark W., Kortas, Samuel, Ladizinsky, Eric, Lai, Tony, Lanting, Trevor, Li, Ryan, MacDonald, Allison J. R., Marsden, Gaelen, McGeoch, Catherine C., Molavi, Reza, Neufeld, Richard, Norouzpour, Mana, Oh, Travis, Pasvolsky, Joel, Poitras, Patrick, Poulin-Lamarre, Gabriel, Prescott, Thomas, Reis, Mauricio, Rich, Chris, Samani, Mohammad, Sheldan, Benjamin, Smirnov, Anatoly, Sterpka, Edward, Clavera, Berta Trullas, Tsai, Nicholas, Volkmann, Mark, Whiticar, Alexander, Whittaker, Jed D., Wilkinson, Warren, Yao, Jason, Yi, T. J., Sandvik, Anders W., Alvarez, Gonzalo, Melko, Roger G., Carrasquilla, Juan, Franz, Marcel, Amin, Mohammad H.
Quantum computers hold the promise of solving certain problems that lie beyond the reach of conventional computers. Establishing this capability, especially for impactful and meaningful problems, remains a central challenge. One such problem is the s
Externí odkaz:
http://arxiv.org/abs/2403.00910
Fine-tuning large pre-trained language models (LLMs) on particular datasets is a commonly employed strategy in Natural Language Processing (NLP) classification tasks. However, this approach usually results in a loss of models generalizability. In thi
Externí odkaz:
http://arxiv.org/abs/2401.16638
Autor:
Afrin, Sadia, Chowdhury, Md. Shahad Mahmud, Islam, Md. Ekramul, Khan, Faisal Ahamed, Chowdhury, Labib Imam, Mahtab, MD. Motahar, Chowdhury, Nazifa Nuha, Forkan, Massud, Kundu, Neelima, Arif, Hakim, Rashid, Mohammad Mamun Or, Amin, Mohammad Ruhul, Mohammed, Nabeel
Lemmatization holds significance in both natural language processing (NLP) and linguistics, as it effectively decreases data density and aids in comprehending contextual meaning. However, due to the highly inflected nature and morphological richness,
Externí odkaz:
http://arxiv.org/abs/2311.03078
Autor:
Amin, Mohammad H., King, Andrew D., Raymond, Jack, Harris, Richard, Bernoudy, William, Berkley, Andrew J., Boothby, Kelly, Smirnov, Anatoly, Altomare, Fabio, Babcock, Michael, Baron, Catia, Connor, Jake, Dehn, Martin, Enderud, Colin, Hoskinson, Emile, Huang, Shuiyuan, Johnson, Mark W., Ladizinsky, Eric, Lanting, Trevor, MacDonald, Allison J. R., Marsden, Gaelen, Molavi, Reza, Oh, Travis, Poulin-Lamarre, Gabriel, Ramp, Hugh, Rich, Chris, Clavera, Berta Trullas, Tsai, Nicholas, Volkmann, Mark, Whittaker, Jed D., Yao, Jason, Heinsdorf, Niclas, Kaushal, Nitin, Nocera, Alberto, Franz, Marcel
Quantum Error Mitigation (QEM) presents a promising near-term approach to reduce error when estimating expectation values in quantum computing. Here, we introduce QEM techniques tailored for quantum annealing, using Zero-Noise Extrapolation (ZNE). We
Externí odkaz:
http://arxiv.org/abs/2311.01306
Autor:
Islam, Md. Ekramul, Chowdhury, Labib, Khan, Faisal Ahamed, Hossain, Shazzad, Hossain, Sourave, Rashid, Mohammad Mamun Or, Mohammed, Nabeel, Amin, Mohammad Ruhul
This study introduces SentiGOLD, a Bangla multi-domain sentiment analysis dataset. Comprising 70,000 samples, it was created from diverse sources and annotated by a gender-balanced team of linguists. SentiGOLD adheres to established linguistic conven
Externí odkaz:
http://arxiv.org/abs/2306.06147