الرئيسية الأخبار أحدث الأوراق البحثية الدروس مجموعات البيانات الموسوعة SOTA نماذج LLM لوحة الأداء GPU الفعاليات

العربية

Data To Text Generation On E2E Nlg Challenge

المقاييس

BLEU

CIDEr

METEOR

NIST

ROUGE-L

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	BLEU	CIDEr	METEOR	NIST	ROUGE-L	Paper Title	Repository
Gong	64.22	2.2721	44.69	8.3453	66.45	Technical Report for E2E NLG Challenge	-
TrICy (trK = 0)	66.43	-	-	-	70.14	TrICy: Trigger-guided Data-to-text Generation with Intent aware Attention-Copy	-
Sys1-Primary	65.61	2.2183	45.17	8.5105	68.39	TNT-NLG, System 1: Using a statistical NLG to massively augment crowd-sourced data for neural generation	-
TGen	65.93	2.2338	44.83	8.6094	68.50	Findings of the E2E NLG Challenge	-
EDA_CS	67.05	2.2355	44.49	8.5150	68.94	Copy mechanism and tailored training for character-based data-to-text generation	-
TUDA	56.57	1.8206	45.29	7.4544	66.14	E2E NLG Challenge: Neural Models vs. Templates
Slug	66.19	-	44.54	8.6130	67.72	A Deep Ensemble Model with Slot Alignment for Sequence-to-Sequence Natural Language Generation	-
Self-memory	65.11	2.16	46.11	8.35	68.41	Self-training from Self-memory in Data-to-text Generation	-
EDA_CS (TL)	65.80	2.1803	45.16	8.5615	67.40	Copy mechanism and tailored training for character-based data-to-text generation	-
Zhang	65.45	2.1012	43.92	8.1804	70.83	Attention Regularized Sequence-to-Sequence Learning for E2E NLG Challenge	-
S_1^R	68.60	2.37	45.25	8.73	70.82	Pragmatically Informative Text Generation	-

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Data To Text Generation On E2E Nlg Challenge | SOTA | HyperAI