OpenCodePapers

data-to-text-generation-on-e2e-nlg-challenge

Data-to-Text Generation
Dataset Link
Results over time
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Leaderboard
PaperCodeBLEUMETEORNISTROUGE-LCIDErNumber of parameters (M)ModelNameReleaseDate
Pragmatically Informative Text Generation✓ Link68.6045.258.7370.822.37S_1^R2019-04-02
Copy mechanism and tailored training for character-based data-to-text generation✓ Link67.0544.498.515068.942.2355EDA_CS2019-04-26
TrICy: Trigger-guided Data-to-text Generation with Intent aware Attention-Copy66.4370.144.7TrICy (trK = 0)2024-01-25
A Deep Ensemble Model with Slot Alignment for Sequence-to-Sequence Natural Language Generation66.1944.548.613067.72Slug2018-05-16
Findings of the E2E NLG Challenge✓ Link65.9344.838.609468.502.2338TGen2018-10-02
Copy mechanism and tailored training for character-based data-to-text generation✓ Link65.8045.168.561567.402.1803EDA_CS (TL)2019-04-26
TNT-NLG, System 1: Using a statistical NLG to massively augment crowd-sourced data for neural generation65.6145.178.510568.392.2183Sys1-Primary2018-04-26
Attention Regularized Sequence-to-Sequence Learning for E2E NLG Challenge65.4543.928.180470.832.1012Zhang2018-03-01
Self-training from Self-memory in Data-to-text Generation✓ Link65.1146.118.3568.412.16Self-memory2024-01-19
Technical Report for E2E NLG Challenge64.2244.698.345366.452.2721Gong2017-12-19
E2E NLG Challenge: Neural Models vs. Templates✓ Link56.5745.297.454466.141.8206TUDA2018-11-01