Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

Automatic Text Summarization (ATS), utilizing Natural Language Processing (NLP)
algorithms, aims to create concise and accurate summaries, thereby significantly reducing …

Large Language Models (LLMs) exhibit remarkably powerful capabilities. One of the crucial
factors to achieve success is aligning the LLM's output with human preferences. This …

While finetuning language models from pairwise preferences has proven remarkably
effective, the underspecified nature of natural language presents critical challenges. Direct …

Environmental conservation organizations routinely monitor news content on conservation
in protected areas to maintain situational awareness of developments that can have an …

Abstractive dialogue summarization is the task of distilling conversations into informative
and concise summaries. Although reviews have been conducted on this topic, there is a lack …

Abstract Summary generation using large language models (LLMs) is characterized by its
flexibility, high quality, and efficiency. However, professional articles usually contain domain …

The task of summarisation has been traditionally a difficult one for the natural language
processing field. The new tools based on large language models such as GPT neural net …