We evaluate recent Large language Models (LLMs) on the challenging task of summarizing
short stories, which can be lengthy, and include nuanced subtext or scrambled timelines …

While long-context large language models (LLMs) can technically summarize book-length
documents (> 100K tokens), the length and complexity of the documents have so far …

Rationality is the quality of being guided by reason, characterized by logical thinking and
decision-making that align with evidence and logical rules. This quality is essential for …

Text summarization research has undergone several significant transformations with the
advent of deep neural networks, pre-trained language models (PLMs), and recent large …

Recent work has explored the capability of large language models (LLMs) to identify and
correct errors in LLM-generated responses. These refinement approaches frequently …

Human evaluation has been the gold standard for checking faithfulness in abstractive
summarization. However, with a challenging source domain like narrative, multiple …

Through the advent of pre-trained language models, there have been notable
advancements in abstractive summarization systems. Simultaneously, a considerable …

Text summarization, a key natural language generation (NLG) task, is vital in various
domains. However, the high cost of inaccurate summaries in risk-critical applications …

Recent large language models (LLMs) can generate and revise text with human-level
performance, and have been widely commercialized in systems like ChatGPT. These …

Accurate text summarization is one of the most common and important tasks performed by
Large Language Models, where the costs of human review for an entire document may be …