arXiv:2609.00241v1 Announce Type: new
Abstract: Long documents often distribute important information across extensive narrative passages and multiple tables, making faithful summarization particular...
By Meng Zhou, Wenhao You, Wei Yuan
arXiv:2607. 10212v1 Announce Type: new Abstract: Knowledge Graphs (KGs) are increasingly constructed through automated extraction pipelines; however, such systems often introduce spurious or incomplete triples, which degrade downstream performance.
By Nipun Misra, Vikranth Udandarao, Aanchal Gupta, Yogender Kumar, Manuj Mukherjee, Raghava Mutharaju
arXiv:2607. 10806v1 Announce Type: cross Abstract: Quantifying abstractiveness in generated summaries is essential for evaluating summarization models beyond surface-level metrics like ROUGE.
By Praveenkumar Katwe, Rakesh Chandra Balabantaray, Kali Prasad Vittala
Knowledge Graphs (KGs) are increasingly constructed through automated extraction pipelines; however, such systems often introduce spurious or incomplete triples, which degrade downstream performance. Existing evaluation practices rely heavily on task-specific metrics or small-scale manual verification, offering limited insight into the structural and semantic fidelity of extracted graphs.
arXiv:2608.28624v1 Announce Type: cross
Abstract: Accurate interpretation of single-visit and longitudinal clinical assessments for Parkinson's disease is time-consuming and often depends on speciali...
By Sana Alamgeera, Denise Goberta, Muhammad Irshad, Anne H. H. Ngu
arXiv:2608.18082v2 Announce Type: replace
Abstract: Although context windows have expanded significantly in recent years, hallucinations in long-context summarization remain a challenge. Long novels...
By Ruizhi Zhang, Jinwei Chen, Xiangju Lu, He Yan, Mo Yu, Junmin Zhu, Wei Zhang