Zobrazeno 1 - 10
of 32 440
pro vyhledávání: '"RAZAK, A."'
Accurate identification of strawberries during their maturing stages is crucial for optimizing yield management, and pest control, and making informed decisions related to harvest and post-harvest logistics. This study evaluates the performance of YO
Externí odkaz:
http://arxiv.org/abs/2408.05661
Autor:
Razak, Aisyah, Nazhan, Ariff, Adha, Kamarul, Adzlan, Wan Adzhar Faiq, Ahmad, Mas Aisyah, Azman, Ammar
As large language models (LLMs) become increasingly integrated into operational workflows (LLM-Ops), there is a pressing need for effective guardrails to ensure safe and aligned interactions, including the ability to detect potentially unsafe or inap
Externí odkaz:
http://arxiv.org/abs/2407.20729
Autor:
Williams, Ben, van Merriënboer, Bart, Dumoulin, Vincent, Hamer, Jenny, Triantafillou, Eleni, Fleishman, Abram B., McKown, Matthew, Munger, Jill E., Rice, Aaron N., Lillis, Ashlee, White, Clemency E., Hobbs, Catherine A. D., Razak, Tries B., Jones, Kate E., Denton, Tom
Machine learning has the potential to revolutionize passive acoustic monitoring (PAM) for ecological assessments. However, high annotation and compute costs limit the field's efficacy. Generalizable pretrained networks can overcome these costs, but h
Externí odkaz:
http://arxiv.org/abs/2404.16436
Our contribution introduces a groundbreaking multimodal large language model designed to comprehend multi-images, multi-audio, and multi-images-multi-audio within a single multiturn session. Leveraging state-of-the-art models, we utilize the SigLIP e
Externí odkaz:
http://arxiv.org/abs/2402.11297
In this work, we present a comprehensive exploration of finetuning Malaysian language models, specifically Llama2 and Mistral, on embedding tasks involving negative and positive pairs. We release two distinct models tailored for Semantic Similarity a
Externí odkaz:
http://arxiv.org/abs/2402.03053
Autor:
Fang, Congyu, Dziedzic, Adam, Zhang, Lin, Oliva, Laura, Verma, Amol, Razak, Fahad, Papernot, Nicolas, Wang, Bo
Publikováno v:
eBioMedicine, vol. 101, p. 105006, 2024
Machine Learning (ML) has demonstrated its great potential on medical data analysis. Large datasets collected from diverse sources and settings are essential for ML models in healthcare to achieve better accuracy and generalizability. Sharing data ac
Externí odkaz:
http://arxiv.org/abs/2402.00205
Addressing the gap in Large Language Model pretrained from scratch with Malaysian context, We trained models with 1.1 billion, 3 billion, and 5 billion parameters on a substantial 349GB dataset, equivalent to 90 billion tokens based on our pretrained
Externí odkaz:
http://arxiv.org/abs/2401.14680
In this paper, we present significant advancements in the pretraining of Mistral 7B, a large-scale language model, using a dataset of 32.6 GB, equivalent to 1.1 billion tokens. We explore the impact of extending the context length, releasing models w
Externí odkaz:
http://arxiv.org/abs/2401.13565
Autor:
Razak, Nur Ain Shuhada Ab, Habib, Syahir, Shukor, Mohd Yunus Abd, Alias, Siti Aisyah, Smykla, Jerzy, Yasid, Nur Adeela
Despite its remoteness from other continents, the Antarctic region cannot escape the aftermath of human activities as it is highly influenced by anthropogenic impacts that occur both in the regional and global context. Contamination by microplastics,
Externí odkaz:
http://arxiv.org/abs/2401.02096
Publikováno v:
Kybernetes, 2023, Vol. 53, Issue 11, pp. 4359-4380.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/K-11-2022-1572
