From generation to judgment: Opportunities and challenges of llm-as-a-judge

D Li, B Jiang, L Huang, A Beigi, C Zhao, Z Tan… - arxiv preprint arxiv …, 2024 - arxiv.org
Assessment and evaluation have long been critical challenges in artificial intelligence (AI)
and natural language processing (NLP). However, traditional methods, whether matching …

Business insights using RAG–LLMs: a review and case study

M Arslan, S Munawar, C Cruz - Journal of Decision Systems, 2024 - Taylor & Francis
As organizations increasingly rely on diverse data sources like invoices and surveys,
efficient Information Extraction (IE) is crucial. Natural Language Processing (NLP) enhances …

Benchmarking retrieval-augmented generation for medicine

G **ong, Q **, Z Lu, A Zhang - arxiv preprint arxiv:2402.13178, 2024 - arxiv.org
While large language models (LLMs) have achieved state-of-the-art performance on a wide
range of medical question answering (QA) tasks, they still face challenges with …

Medadapter: Efficient test-time adaptation of large language models towards medical reasoning

W Shi, R Xu, Y Zhuang, Y Yu, H Sun, H Wu… - arxiv preprint arxiv …, 2024 - arxiv.org
Despite their improved capabilities in generation and reasoning, adapting large language
models (LLMs) to the biomedical domain remains challenging due to their immense size …

Custom Large Language Models Improve Accuracy: Comparing Retrieval Augmented Generation and Artificial Intelligence Agents to Noncustom Models for Evidence …

JJ Woo, AJ Yang, RJ Olsen, SS Hasan… - … : The Journal of …, 2024 - Elsevier
Purpose The purpose of the study is to demonstrate the value of custom methods, namely
Retrieval Augmented Generation (RAG)-based Large Language Models (LLMs) and Agentic …

[HTML][HTML] Driving sustainable energy transitions with a multi-source RAG-LLM system

M Arslan, L Mahdjoubi, S Munawar - Energy and Buildings, 2024 - Elsevier
By 2035, the UK aims to upgrade all homes to achieve a net-zero economy by 2050, thereby
reducing energy consumption, household costs, and improving living conditions. Small and …

Ram-ehr: Retrieval augmentation meets clinical predictions on electronic health records

R Xu, W Shi, Y Yu, Y Zhuang, B **, MD Wang… - arxiv preprint arxiv …, 2024 - arxiv.org
We present RAM-EHR, a Retrieval AugMentation pipeline to improve clinical predictions on
Electronic Health Records (EHRs). RAM-EHR first collects multiple knowledge sources …

Clinical insights: A comprehensive review of language models in medicine

N Neveditsin, P Lingras, V Mago - arxiv preprint arxiv:2408.11735, 2024 - arxiv.org
This paper provides a detailed examination of the advancements and applications of large
language models in the healthcare sector, with a particular emphasis on clinical …

OPEN-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models

SB Islam, MA Rahman, KSM Hossain, E Hoque… - arxiv preprint arxiv …, 2024 - arxiv.org
Retrieval-Augmented Generation (RAG) has been shown to enhance the factual accuracy of
Large Language Models (LLMs), but existing methods often suffer from limited reasoning …

Political-RAG: using generative AI to extract political information from media content

M Arslan, S Munawar, C Cruz - Journal of Information Technology …, 2024 - Taylor & Francis
In the digital era, media content is crucial for political analysis, providing valuable insights
through news articles, social media posts, speeches, and reports. Natural Language …