Question Answering on ELI5

Metric: Rouge-1 (higher is better)

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#	Model↕	Rouge-1▼	Extra Data	Paper	Date↕	Code
1	BART	30.6	No	BART: Denoising Sequence-to-Sequence Pre-trainin...	2019-10-29	Code
2	E-MCA	30	No	Using Local Knowledge Graph Construction to Scal...	2019-10-18	Code
3	Transformer Multitask + LayerDrop	29.4	No	Reducing Transformer Depth on Demand with Struct...	2019-09-25	Code
4	QG	29.15	No	Closed-book Question Generation via Contrastive ...	2022-10-13	Code
5	Multi-Inrerleave	23.32	No	Improving Conditioning in Context-Aware Sequence...	2019-11-21	-

#1BARTSOTA
30.6
Rouge-1· 2019-10-29
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension Code
#2E-MCASOTA
30
Rouge-1· 2019-10-18
Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs Code
#3Transformer Multitask + LayerDropSOTA
29.4
Rouge-1· 2019-09-25
Reducing Transformer Depth on Demand with Structured Dropout Code
#4QG
29.15
Rouge-1· 2022-10-13
Closed-book Question Generation via Contrastive Learning Code
#5Multi-Inrerleave
23.32
Rouge-1· 2019-11-21
Improving Conditioning in Context-Aware Sequence to Sequence Models