End-To-End Dialogue Modelling

7 papers with code • 2 benchmarks • 3 datasets

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Most implemented papers

Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context

ucdavisnlp/damd-multiwoz 24 Nov 2019

Conversations have an intrinsic one-to-many property, which means that multiple responses can be appropriate for the same dialog context.

Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System

awslabs/pptod ACL 2022

Pre-trained language models have been recently shown to benefit task-oriented dialogue (TOD) systems.

A Simple Language Model for Task-Oriented Dialogue

salesforce/simpletod NeurIPS 2020

Task-oriented dialogue is often decomposed into three tasks: understanding user input, deciding actions, and generating a response.

A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning

thu-spmi/LABES EMNLP 2020

In this paper we aim at alleviating the reliance on belief state labels in building end-to-end dialog systems, by leveraging unlabeled dialog data towards semi-supervised learning.

AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Models

ufal/augpt EMNLP (NLP4ConvAI) 2021

Our model substantially outperforms the baseline on the MultiWOZ data and shows competitive performance with state of the art in both automatic and human evaluation.

Maintaining Common Ground in Dynamic Environments

Alab-NII/dynamic-onecommon 29 May 2021

Common grounding is the process of creating and maintaining mutual understandings, which is a critical aspect of sophisticated human communication.

GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injection

siat-nlp/galaxy 29 Nov 2021

Pre-trained models have proved to be powerful in enhancing task-oriented dialog systems.