3 papers
cs.CL2024
AdaptEval: Evaluating Large Language Models on Domain Adaptation for Text Summarization
Anum Afzal, Ribin Chalumattu, Florian Matthes +1
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 do…
cs.CL2024
Which Information Matters? Dissecting Human-written Multi-document Summaries with Partial Information Decomposition
Laura Mascarell, Yan L'Homme, Majed El Helou
Understanding the nature of high-quality summaries is crucial to further improve the performance of multi-document summarization. We propose an approach to characterize human-writt…
cs.CL2024
German also Hallucinates! Inconsistency Detection in News Summaries with the Absinth Dataset
Laura Mascarell, Ribin Chalumattu, Annette Rios
The advent of Large Language Models (LLMs) has led to remarkable progress on a wide range of natural language processing tasks. Despite the advances, these large-sized models still…