Home News Latest Papers Tutorials Datasets Wiki SOTA LLM Models GPU Leaderboard Events

English

Question Answering On Narrativeqa

Metrics

BLEU-1

BLEU-4

METEOR

Rouge-L

Results

Performance results of various models on this benchmark

Model Name	BLEU-1	BLEU-4	METEOR	Rouge-L	Paper Title	Repository
Masque (NarrativeQA only)	48.7	20.98	21.95	54.74	Multi-style Generative Reading Comprehension	-
MHPGM + NOIC	43.63	21.07	19.03	44.16	Commonsense for Generative Multi-Hop Question Answering Tasks
DecaProp	44.35	27.61	21.80	44.69	Densely Connected Attention Propagation for Reading Comprehension
BERT-QA with Hard EM objective	-	-	-	58.8	A Discrete Hard EM Approach for Weakly Supervised Question Answering
FiD+Distil	35.3	7.5	11.1	32	Distilling Knowledge from Reader to Retriever for Question Answering
ConZNet	42.76	22.49	19.24	46.67	Cut to the Chase: A Context Zoom-in Network for Reading Comprehension	-
Masque (NarrativeQA + MS MARCO)	54.11	30.43	26.13	59.87	Multi-style Generative Reading Comprehension	-
Oracle IR Models	54.60/55.55	26.71/27.78	-	-	The NarrativeQA Reading Comprehension Challenge
BiAttention + DCU-LSTM	36.55	19.79	17.87	41.44	Multi-Granular Sequence Encoding via Dilated Compositional Units for Reading Comprehension	-
BiDAF	33.45	15.69	15.68	36.74	Bidirectional Attention Flow for Machine Comprehension

0 of 10 row(s) selected.