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Found 5 papers, 2 papers with code
Towards Optimizing a Retrieval Augmented Generation using Large Language Model on Academic Data
Given the growing trend of many organizations integrating Retrieval Augmented Generation (RAG) into their operations, we assess RAG on domain-specific data and test state-of-the-art models across various optimization techniques.
AdaptEval: Evaluating Large Language Models on Domain Adaptation for Text Summarization
Despite the advances in the abstractive summarization task using Large Language Models (LLM), there is a lack of research that asses their abilities to easily adapt to different domains.
Towards Optimizing and Evaluating a Retrieval Augmented QA Chatbot using LLMs with Human in the Loop
Large Language Models have found application in various mundane and repetitive tasks including Human Resource (HR) support.
Challenges in Domain-Specific Abstractive Summarization and How to Overcome them
Large Language Models work quite well with general-purpose data and many tasks in Natural Language Processing.
Investigating Conversational Search Behavior For Domain Exploration
Conversational search has evolved as a new information retrieval paradigm, marking a shift from traditional search systems towards interactive dialogues with intelligent search agents.
