33 citations · 134 across the 22 of their papers we have counts for
4 papers · 1 filter
Knowledge Graph Generation From Text
Igor Melnyk, Pierre Dognin, Payel Das
In this work we propose a novel end-to-end multi-stage Knowledge Graph (KG) generation system from textual inputs, separating the overall process into two stages. The graph nodes a…
ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language Models
Pierre L. Dognin, Inkit Padhi, Igor Melnyk +1
Automatic construction of relevant Knowledge Bases (KBs) from text, and generation of semantically meaningful text from KBs are both long-standing goals in Machine Learning. In thi…
DualTKB: A Dual Learning Bridge between Text and Knowledge Base
Pierre L. Dognin, Igor Melnyk, Inkit Padhi +2
In this work, we present a dual learning approach for unsupervised text to path and path to text transfers in Commonsense Knowledge Bases (KBs). We investigate the impact of weak s…
Learning Implicit Text Generation via Feature Matching
Inkit Padhi, Pierre Dognin, Ke Bai +4
Generative feature matching network (GFMN) is an approach for training implicit generative models for images by performing moment matching on features from pre-trained neural netwo…