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Denoising Pre-Training and Data Augmentation Strategies for Enhanced RDF Verbalization with Transformers

2020-12-01 · ACL (WebNLG, INLG) 2020 12 · Sebastien Montella, Betty Fabre, Tanguy Urvoy, Johannes Heinecke, Lina Rojas-Barahona

The task of verbalization of RDF triples has known a growth in popularity due to the rising ubiquity of Knowledge Bases (KBs). The formalism of RDF triples is a simple and efficient way to store facts at a large scale. However, its abstract representation makes it difficult for humans to interpret. For this purpose, the WebNLG challenge aims at promoting automated RDF-to-text generation. We propose to leverage pre-trainings from augmented data with the Transformer model using a data augmentation strategy. Our experiment results show a minimum relative increases of 3.73%, 126.05% and 88.16% in BLEU score for seen categories, unseen entities and unseen categories respectively over the standard training.

📄 PDF Abstract BibTeX arXiv:2012.00571

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Tasks

Data Augmentation Denoising Text Generation

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Augraphy: A Data Augmentation Library for Document Images

2022-08-30 · Alexander Groleau, Kok Wei Chee, Stefan Larson, Samay Maini 외

This paper introduces Augraphy, a Python library for constructing data augmentation pipelines which produce distortions commonly seen in real-world document image datasets. Augraphy stands apart from other data augmentat…

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Diffusion-Driven Synthetic Tabular Data Generation for Enhanced DoS/DDoS Attack Classification

2026-01-19 · Aravind B, Anirud R. S., Sai Surya Teja N, Bala Subrahmanya Sriranga Navaneeth A 외 arxiv

Class imbalance refers to a situation where certain classes in a dataset have significantly fewer samples than oth- ers, leading to biased model performance. Class imbalance in network intrusion detection using Tabular D…

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Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving Augmentation

2019-04-29 · Jiaming Liu, Chi-Hao Wu, Yuzhi Wang, Qin Xu 외

In this paper, we present new data pre-processing and augmentation techniques for DNN-based raw image denoising. Compared with traditional RGB image denoising, performing this task on direct camera sensor readings presen…

Data Augmentation Denoising Image Augmentation Image Denoising+2

Structuring a Training Strategy to Robustify Perception Models with Realistic Image Augmentations

2024-08-30 · Ahmed Hammam, Bharathwaj Krishnaswami Sreedhar, Nura Kawa, Tim Patzelt 외

Advancing Machine Learning (ML)-based perception models for autonomous systems necessitates addressing weak spots within the models, particularly in challenging Operational Design Domains (ODDs). These are environmental …

Autonomous Driving Hyperparameter Optimization object-detection Object Detection+1

Ali-AUG: Innovative Approaches to Labeled Data Augmentation using One-Step Diffusion Model

2024-10-24 · Ali Hamza, Aizea Lojo, Adrian Núñez-Marcos, Aitziber Atutxa

This paper introduces Ali-AUG, a novel single-step diffusion model for efficient labeled data augmentation in industrial applications. Our method addresses the challenge of limited labeled data by generating synthetic, l…

Data Augmentation Image Generation