no code implementations • 16 Jul 2024 • Garima Agrawal, Tharindu Kumarage, Zeyad Alghamdi, Huan Liu
Large Language Models (LLMs) are proficient at generating coherent and contextually relevant text but face challenges when addressing knowledge-intensive queries in domain-specific and factual question-answering tasks.
no code implementations • 2 Mar 2024 • Tharindu Kumarage, Garima Agrawal, Paras Sheth, Raha Moraffah, Aman Chadha, Joshua Garland, Huan Liu
We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text.
no code implementations • 14 Nov 2023 • Garima Agrawal, Tharindu Kumarage, Zeyad Alghamdi, Huan Liu
The contemporary LLMs are prone to producing hallucinations, stemming mainly from the knowledge gaps within the models.
1 code implementation • CEUR Workshop Proceedings (CEUR-WS.org) 2023 • Garima Agrawal, Kuntal Pal, Yuli Deng, Huan Liu and Chitta Baral
This dataset can be used to construct knowledge graphs to teach cybersecurity and promote cognitive learning.
no code implementations • 10 Sep 2022 • Garima Agrawal, Anindya Goswami
We model the stock price dynamics through a semi-Markov process obtained using a Poisson random measure.