HyperAI
HyperAI超神经
首页
算力平台
文档
资讯
论文
教程
数据集
百科
SOTA
LLM 模型天梯
GPU 天梯
顶会
开源项目
全站搜索
关于
中文
HyperAI
HyperAI超神经
Toggle sidebar
全站搜索…
⌘
K
Command Palette
Search for a command to run...
首页
SOTA
文档摘要
Document Summarization On Cnn Daily Mail
Document Summarization On Cnn Daily Mail
评估指标
PPL
ROUGE-1
ROUGE-2
ROUGE-L
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
PPL
ROUGE-1
ROUGE-2
ROUGE-L
Paper Title
Repository
Scrambled code + broken (alter)
-
48.18
19.84
45.35
Universal Evasion Attacks on Summarization Scoring
PEGASUS + SummaReranker
-
47.16
22.55
43.87
SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization
Fourier Transformer
-
44.76
21.55
41.34
Fourier Transformer: Fast Long Range Modeling by Removing Sequence Redundancy with FFT Operator
GLM-XXLarge
-
44.7
21.4
41.4
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
HAT-BART
-
44.48
21.31
41.52
Hierarchical Learning for Generation with Long Source Sequences
-
MatchSum (RoBERTa-base)
-
44.41
20.86
40.55
Extractive Summarization as Text Matching
Hie-BART
-
44.35
21.37
41.05
Hie-BART: Document Summarization with Hierarchical BART
-
MatchSum (BERT-base)
-
44.22
20.62
40.38
Extractive Summarization as Text Matching
BertSumExt
-
43.85
20.34
39.9
Text Summarization with Pretrained Encoders
BigBird-Pegasus
-
43.84
21.11
40.74
Big Bird: Transformers for Longer Sequences
T5-11B
-
43.52
21.55
40.69
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
BERTSUM+Transformer
-
43.25
20.24
39.63
Fine-tune BERT for Extractive Summarization
UniLM (Abstractive Summarization)
-
43.08
20.43
40.34
Unified Language Model Pre-training for Natural Language Understanding and Generation
Selector+Pointer Generator
-
41.72
18.74
38.79
Mixture Content Selection for Diverse Sequence Generation
NeuSUM
-
41.59
19.01
37.98
Neural Document Summarization by Jointly Learning to Score and Select Sentences
Bottom-Up Sum
32.75
41.22
18.68
38.34
Bottom-Up Abstractive Summarization
TaLK Convolutions (Deep)
-
40.59
18.97
36.81
Time-aware Large Kernel Convolutions
Lead-3
-
40.34
17.70
36.57
Get To The Point: Summarization with Pointer-Generator Networks
TaLK Convolutions (Standard)
-
40.03
18.45
36.13
Time-aware Large Kernel Convolutions
ML + RL (Paulus et al., 2017)
-
39.87
15.82
36.90
A Deep Reinforced Model for Abstractive Summarization
0 of 26 row(s) selected.
Previous
Next
Document Summarization On Cnn Daily Mail | SOTA | HyperAI超神经