RST-LoRA: A Discourse-Aware Low-Rank Adaptation for Long Document Abstractive Summarization
D Pu, V Demberg - arXiv preprint arXiv:2405.00657, 2024 - arxiv.org
For long document summarization, discourse structure is important to discern the key
content of the text and the differences in importance level between sentences. Unfortunately …
content of the text and the differences in importance level between sentences. Unfortunately …
Knowledge-Centric Templatic Views of Documents
I Cachola, S Cucerzan, A Herring, V Mijovic… - arXiv preprint arXiv …, 2024 - arxiv.org
Authors seeking to communicate with broader audiences often compose their ideas about
the same underlying knowledge in different documents and formats--for example, as slide …
the same underlying knowledge in different documents and formats--for example, as slide …
FENICE: Factuality Evaluation of summarization based on Natural language Inference and Claim Extraction
Recent advancements in text summarization, particularly with the advent of Large Language
Models (LLMs), have shown remarkable performance. However, a notable challenge …
Models (LLMs), have shown remarkable performance. However, a notable challenge …
Understanding Position Bias Effects on Fairness in Social Multi-Document Summarization
O Olabisi, A Agrawal - arXiv preprint arXiv:2405.01790, 2024 - arxiv.org
Text summarization models have typically focused on optimizing aspects of quality such as
fluency, relevance, and coherence, particularly in the context of news articles. However …
fluency, relevance, and coherence, particularly in the context of news articles. However …
Multilingual Generation in Abstractive Summarization: A Comparative Study
J Li, J Chen, H Chen, D Zhao… - Proceedings of the 2024 …, 2024 - aclanthology.org
The emergence of pre-trained models marks a significant juncture for the multilingual
generation, offering unprecedented capabilities to comprehend and produce text across …
generation, offering unprecedented capabilities to comprehend and produce text across …