Data-to-Text generation with loosely aligned WikiBio dataset from (Lebret et al. 2016). Explicit content selection step with Multi-Instance Learning.
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Updated
Aug 8, 2018 - Lua
Data-to-Text generation with loosely aligned WikiBio dataset from (Lebret et al. 2016). Explicit content selection step with Multi-Instance Learning.
Data To Text! Your ultimate open source solution to build NLG systems.
Implementation of NeurIPS 20 paper: Latent Template Induction with Gumbel-CRFs
Codebase for the journal paper "The Rare Word Issue in Natural Language Generation: a Character-Based Solution" (Giovanni Bonetta, Marco Roberti, Rossella Cancelliere, Patrick Gallinari)
Code for Describing a Knowledge Base
Code and Data for EMNLP2020 Paper "KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation"
data-to-text system based on change point detection and fuzzy set theory.
TCube generates rich and fluent narratives that describes the characteristics, trends, and anomalies of any time-series data (domain-agnostic) using the transfer learning capabilities of PLMs.
SPRING is a seq2seq model for Text-to-AMR and AMR-to-Text (AAAI2021).
🧐 Code & Data for Fact-based Text Editing (Iso et al; ACL 2020)
⛹️Code for Learning to Select, Track, and Generate for Data-to-Text (Iso et al; ACL 2019).
🏀 Script for generating the rotowire-modified dataset (Iso et al; ACL 2019)
Code for SAPPHIRE: Approaches for Enhanced Concept-to-Text Generation (https://aclanthology.org/2021.inlg-1.21/) INLG 2021 Best Long Paper.
Biomedical Data-to-Text Generation via Fine-Tuning Transformers
Data-to-text generation papers
This repository is the official implementation of our paper MVP: Multi-task Supervised Pre-training for Natural Language Generation.
Code for IJCoL 7 Special Issue Paper - Improving Data-to-Text Generation via Preserving High-Frequency Phrases and Fact-Checking
This repository is the official implementation of our paper MVP: Multi-task Supervised Pre-training for Natural Language Generation.
[COLING22] Text-to-Text Extraction and Verbalization of Biomedical Event Graphs
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