sequence-to-sequence model. It encapsulates the key information from the entire input sequence and serves as a condensed representation. This last hidden state is crucial in summarization tasks, as it is used as
In this exposition, we unveil the impact of modified reinforcement learning from human feedback (RLHF) and Reinforcement Learning from AI Feedback (RLAIF) on text summarization problems. The main focus is to bring the key highlights from this learning process to researchers for an easier ...
This study examines the interplay between text summarization techniques and embeddings from Language Models (LMs) in constructing expert systems dedicated
This paper embarks on an exploration into the Large Language Model (LLM) datasets, which play a crucial role in the remarkable advancements of LLMs. The datasets serve as the foundational infrastructure analogous to a root system that sustains and nurtures the development of LLMs. Consequently, ...
Text-Summarization-How-to-Calculate-BertScore The development of machine learning has led to the rapid growth of technological fields such as Natural Language Processing (NLP) and Large Language Models (LLMs). However, with the advancement of these fields, a new problem has emerged: How reliable...
The results of an LLM are then compared with those of a qualified medical teacher and with responses from other LLMs. The Fleiss’ Kappa Test was used to determine the concordance between four responders (3 LLMs + 1 Medical Teacher). In case of poor agreement between responders, Cohen...
(open access) on both sentence-level and document-level materials information extraction. Moreover, the method can leverage online LLM APIs, which allows users to train bespoke models without extensive knowledge of how LLMs work internally; the LLM may be simply treated by the user as a black...
In this summarization task, we train the model to simplify complex information from different technology and commercial data sets. The goal is to teach the model to summarize detailed information into concise and clear terms, whether it’s about patents, product classifications, inventions, or produc...
In recent years, the field of NLP has witnessed substantial advancements owing to the emergence of Large Language Models (LLMs) and Generative AI models [12]. Consequently, there has been a growing interest in leveraging these techniques to tackle problems in the microbiome field as well [13,...
The rapid growth of textual data in the digital agehas necessitated the development of efficient Text Summarization systems to distill critical information from extensive documents. Thisstudy presents a metric-driven comprehensive comparative analysis ofthree state-of-the-art Large Language Models (LLMs)...