2 citations · 5 across the 4 of their papers we have counts for
6 papers · 1 filter
Aging Memories Generate More Fluent Dialogue Responses with Memory Augmented Neural Networks
Omar U. Florez, Erik Mueller
Memory Networks have emerged as effective models to incorporate Knowledge Bases (KB) into neural networks. By storing KB embeddings into a memory component, these models can learn…
Adversarial Bootstrapping for Dialogue Model Training
Oluwatobi Olabiyi, Erik T. Mueller, Christopher Larson +1
Open domain neural dialogue models, despite their successes, are known to produce responses that lack relevance, diversity, and in many cases coherence. These shortcomings stem fro…
DLGNet: A Transformer-based Model for Dialogue Response Generation
Oluwatobi Olabiyi, Erik T. Mueller
Neural dialogue models, despite their successes, still suffer from lack of relevance, diversity, and in many cases coherence in their generated responses. These issues can attribut…
An Adversarial Learning Framework For A Persona-Based Multi-Turn Dialogue Model
Oluwatobi Olabiyi, Anish Khazane, Alan Salimov +1
In this paper, we extend the persona-based sequence-to-sequence (Seq2Seq) neural network conversation model to a multi-turn dialogue scenario by modifying the state-of-the-art hred…
A Persona-based Multi-turn Conversation Model in an Adversarial Learning Framework
Oluwatobi O. Olabiyi, Anish Khazane, Erik T. Mueller
In this paper, we extend the persona-based sequence-to-sequence (Seq2Seq) neural network conversation model to multi-turn dialogue by modifying the state-of-the-art hredGAN archite…
Multi-turn Dialogue Response Generation in an Adversarial Learning Framework
Oluwatobi Olabiyi, Alan Salimov, Anish Khazane +1
We propose an adversarial learning approach for generating multi-turn dialogue responses. Our proposed framework, hredGAN, is based on conditional generative adversarial networks (…