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pro vyhledávání: '"Upadhayay A"'
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing tasks across various domains without needing explicit retraining. This capability, known as In-Context Learning (ICL), while impressive, exposes LLMs to a variety of
Externí odkaz:
http://arxiv.org/abs/2410.11272
Autor:
Upadhayay, Bibek, Behzadan, Vahid
Large Language Models (LLMs) are increasingly being developed and applied, but their widespread use faces challenges. These include aligning LLMs' responses with human values to prevent harmful outputs, which is addressed through safety training meth
Externí odkaz:
http://arxiv.org/abs/2404.07242
Autor:
Upadhayay, Bibek, Behzadan, Vahid
Creating multilingual LLMs poses a significant challenge. Pretraining or fine-tuning LLMs to adopt new languages is evidently very costly. Furthermore, there exist limitations concerning benchmark datasets and the metrics used to measure model perfor
Externí odkaz:
http://arxiv.org/abs/2311.10797
Autor:
Bartholomew Saanu Adeleke, Parul Chaudhary, Modupe Stella Ayilara, Funmilola Mabel Ojo, Sakiru Morenikeji Erinoso, Viabhav Kumar Upadhayay, Adeyemi Isaiah Adeyemo, Saheed Adekunle Akinola
Publikováno v:
Ecologies, Vol 5, Iss 3, Pp 375-401 (2024)
The extreme conditions linked with abiotic stresses have greatly affected soil and plant health. The diverse biochemical activities occurring in the soil environment have been attributed to shaping the dynamics of plant–soil microbiomes by contribu
Externí odkaz:
https://doaj.org/article/c2e9536e08c24b7d80f58aafa3caee07
Autor:
Upadhayay, Bibek, Behzadan, Vahid
Machine learning models are known to be vulnerable to adversarial perturbations in the input domain, causing incorrect predictions. Inspired by this phenomenon, we explore the feasibility of manipulating EEG-based Motor Imagery (MI) Brain Computer In
Externí odkaz:
http://arxiv.org/abs/2211.10033
Autor:
Li, Kevin, Yang, Haoyang, Montoya, Evan, Upadhayay, Anish, Zhou, Zhiyan, Saad-Falcon, Jon, Chau, Duen Horng
Discovering and making sense of relevant literature is fundamental in any scientific field. Node-link diagram-based visualization tools can aid this process; however, existing tools have been evaluated only on small scales. This paper evaluates Argo
Externí odkaz:
http://arxiv.org/abs/2210.13510
Autor:
Yang, Haoyang, Mehta, Pratham Darrpan, Leo, Jonathan, Zhou, Zhiyan, Dass, Megan, Upadhayay, Anish, Slesnick, Timothy C., Shaw, Fawwaz, Randles, Amanda, Chau, Duen Horng
Advanced surgical procedures for congenital heart diseases (CHDs) require precise planning before the surgeries. The conventional approach utilizes 3D-printing and cutting physical heart models, which is a time and resource intensive process. While r
Externí odkaz:
http://arxiv.org/abs/2208.10639
Discovering and making sense of relevant research literature is fundamental to becoming knowledgeable in any scientific discipline. Visualization can aid this process; however, existing tools' adoption and impact have often been constrained, such as
Externí odkaz:
http://arxiv.org/abs/2110.14060
Autor:
Khan, Amir, Singh, Ajay Veer, Kukreti, Bharti, Pandey, Deepali Tiwari, Upadhayay, Viabhav Kumar, Kumar, Rajeew, Goel, Reeta
Publikováno v:
In Science of the Total Environment 1 June 2024 927
Publikováno v:
In Inorganica Chimica Acta 24 May 2024 565