[Retracted] N-GPETS: Neural Attention Graph-Based Pretrained Statistical Model for Extractive Text Summarization

Table 5

ROUGE F1 scores/results on the CNN/DM data set.

Models	CNN/Daily Mail
	R-1	R-2	R-L
Lead-3	40.42	17.62	36.67
Oracle	55.61	32.84	51.88
Non-BERT graph models
NeuSum	41.59	19.01	37.98
HSG	42.31	19.51	38.74
HSG + tri-blocking	42.95	19.76	39.23
BanditSum	41.50	18.70	37.60
JECS	41.70	18.50	37.90
BERT-based graph models
BERTSUM (sent)	43.25	20.24	39.63
HiBERT	42.37	19.95	38.83
DISCOBERT	43.77	20.85	40.67
Topic-GraphSum	44.02	20.81	40.55
DiscoCorrelation-GraphSum (EDU)	43.61	20.81	41.12
N-GPETS (proposed)	44.15	20.86	40.97

The bold values against the model shows that the corresponding model gain the highest performance in comparison to all other models listed in table.