[EMNLP 2022] Unifying and multi-tasking structured knowledge grounding with language models

Code and Data for EMNLP2020 Paper "KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation"

SPRING is a seq2seq model for Text-to-AMR and AMR-to-Text (AAAI2021).

This repository is the official implementation of our paper MVP: Multi-task Supervised Pre-training for Natural Language Generation.

Implementation of NeurIPS 20 paper: Latent Template Induction with Gumbel-CRFs

Code for Describing a Knowledge Base

Biomedical Data-to-Text Generation via Fine-Tuning Transformers

Code for Stage-wise Fine-tuning for Graph-to-Text Generation

🧐 Code & Data for Fact-based Text Editing (Iso et al; ACL 2020)

Code for Controlling Hallucinations at Word Level in Data-to-Text Generation (C. Rebuffel, M. Roberti, L. Soulier, G. Scoutheeten, R. Cancelliere, P. Gallinari)

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.

⛹️Code for Learning to Select, Track, and Generate for Data-to-Text (Iso et al; ACL 2019).

[COLING22] Text-to-Text Extraction and Verbalization of Biomedical Event Graphs

🏀 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.

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 generation papers

Code for my Master Thesis project on "Prompting Techniques for Natural Language Generation in the Medical Domain" at the University of Bologna

data-to-text system based on change point detection and fuzzy set theory.

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)