Zobrazeno 1 - 10
of 1 653
pro vyhledávání: '"P. Wasi"'
Autor:
Romanou, Angelika, Foroutan, Negar, Sotnikova, Anna, Chen, Zeming, Nelaturu, Sree Harsha, Singh, Shivalika, Maheshwary, Rishabh, Altomare, Micol, Haggag, Mohamed A., A, Snegha, Amayuelas, Alfonso, Amirudin, Azril Hafizi, Aryabumi, Viraat, Boiko, Danylo, Chang, Michael, Chim, Jenny, Cohen, Gal, Dalmia, Aditya Kumar, Diress, Abraham, Duwal, Sharad, Dzenhaliou, Daniil, Florez, Daniel Fernando Erazo, Farestam, Fabian, Imperial, Joseph Marvin, Islam, Shayekh Bin, Isotalo, Perttu, Jabbarishiviari, Maral, Karlsson, Börje F., Khalilov, Eldar, Klamm, Christopher, Koto, Fajri, Krzemiński, Dominik, de Melo, Gabriel Adriano, Montariol, Syrielle, Nan, Yiyang, Niklaus, Joel, Novikova, Jekaterina, Ceron, Johan Samir Obando, Paul, Debjit, Ploeger, Esther, Purbey, Jebish, Rajwal, Swati, Ravi, Selvan Sunitha, Rydell, Sara, Santhosh, Roshan, Sharma, Drishti, Skenduli, Marjana Prifti, Moakhar, Arshia Soltani, Moakhar, Bardia Soltani, Tamir, Ran, Tarun, Ayush Kumar, Wasi, Azmine Toushik, Weerasinghe, Thenuka Ovin, Yilmaz, Serhan, Zhang, Mike, Schlag, Imanol, Fadaee, Marzieh, Hooker, Sara, Bosselut, Antoine
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal value of generative AI tools in many communities. However, the developmen
Externí odkaz:
http://arxiv.org/abs/2411.19799
Autor:
Kuhar, Sachit, Ahmad, Wasi Uddin, Wang, Zijian, Jain, Nihal, Qian, Haifeng, Ray, Baishakhi, Ramanathan, Murali Krishna, Ma, Xiaofei, Deoras, Anoop
Recent advancements in code completion models have primarily focused on local file contexts. However, these studies do not fully capture the complexity of real-world software development, which often requires the use of rapidly-evolving public librar
Externí odkaz:
http://arxiv.org/abs/2412.04478
Graph Neural Networks (GNNs) have recently gained traction in transportation, bioinformatics, language and image processing, but research on their application to supply chain management remains limited. Supply chains are inherently graph-like, making
Externí odkaz:
http://arxiv.org/abs/2411.08550
Autor:
Islam, Mst Rafia, Wasi, Azmine Toushik
Publikováno v:
Harms and Risks of AI in the Military Workshop 2024
AI has made significant strides recently, leading to various applications in both civilian and military sectors. The military sees AI as a solution for developing more effective and faster technologies. While AI offers benefits like improved operatio
Externí odkaz:
http://arxiv.org/abs/2411.06336
Climate change poses critical challenges globally, disproportionately affecting low-income countries that often lack resources and linguistic representation on the international stage. Despite Bangladesh's status as one of the most vulnerable nations
Externí odkaz:
http://arxiv.org/abs/2410.17225
Exploring Possibilities of AI-Powered Legal Assistance in Bangladesh through Large Language Modeling
Purpose: Bangladesh's legal system struggles with major challenges like delays, complexity, high costs, and millions of unresolved cases, which deter many from pursuing legal action due to lack of knowledge or financial constraints. This research see
Externí odkaz:
http://arxiv.org/abs/2410.17210
Publikováno v:
Asian Conference on Computer Vision 2024, Lecture Notes in Computer Science (Volume 15475)
Reliable facial expression learning (FEL) involves the effective learning of distinctive facial expression characteristics for more reliable, unbiased and accurate predictions in real-life settings. However, current systems struggle with FEL tasks be
Externí odkaz:
http://arxiv.org/abs/2410.15927
Autor:
Brooks, Alex, Marshall, Philip, Ozog, David, Rahman, Md. Wasi-ur, Stewart, Lawrence, Tom, Rithwik
Modern high-end systems are increasingly becoming heterogeneous, providing users options to use general purpose Graphics Processing Units (GPU) and other accelerators for additional performance. High Performance Computing (HPC) and Artificial Intelli
Externí odkaz:
http://arxiv.org/abs/2409.20476
Autor:
Wasi, Azmine Toushik
Publikováno v:
Proceedings of the 1st Workshop on Knowledge Graphs and Large Language Models (KaLLM 2024), Association for Computational Linguistics 2024
Knowledge Graphs (KGs) serving as semantic networks, prove highly effective in managing complex interconnected data in different domains, by offering a unified, contextualized, and structured representation with flexibility that allows for easy adapt
Externí odkaz:
http://arxiv.org/abs/2408.13521
While Large Language Models (LLM) have created a massive technological impact in the past decade, allowing for human-enabled applications, they can produce output that contains stereotypes and biases, especially when using low-resource languages. Thi
Externí odkaz:
http://arxiv.org/abs/2407.18376