Example of Denoising Task with Consecutive Token Masking

Span-Based Denoising as an Encoder-Decoder Training Objective

Input Corruption Methods for Denoising Autoencoder Training

Denoising Autoencoder Training Objective

Loss Calculation for Encoder-Decoder Denoising Tasks

Training Efficiency in Denoising Autoencoding

Flexibility of Masked Language Modeling for Encoder-Decoder Training

Example of a Denoising Autoencoder Task for Encoder-Decoder Models

BART Model's Use of Diverse Input Corruption Methods

An encoder-decoder model is being trained using the following example:

• Input to Encoder: "The scientist carefully [MASK] the solution into the beaker."
• Target Output for Decoder: "The scientist carefully poured the solution into the beaker."

Based on this training setup, what is the primary function of the decoder?

Evaluating a Model Training Objective

An encoder-decoder model is being trained with the objective of reconstructing a full, original sentence from an input version where several random words have been removed. What is the most critical function of the encoder's output in this specific training paradigm?

Corrupted Input for Encoder-Decoder Pre-training

Diagrammatic Example of an Encoder-Decoder Model Trained with a Denoising Autoencoding Objective