Target-Guided Open-Domain Conversation Planning

09/20/2022
by   Yosuke Kishinami, et al.
0

Prior studies addressing target-oriented conversational tasks lack a crucial notion that has been intensively studied in the context of goal-oriented artificial intelligence agents, namely, planning. In this study, we propose the task of Target-Guided Open-Domain Conversation Planning (TGCP) task to evaluate whether neural conversational agents have goal-oriented conversation planning abilities. Using the TGCP task, we investigate the conversation planning abilities of existing retrieval models and recent strong generative models. The experimental results reveal the challenges facing current technology.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/28/2019

Target-Guided Open-Domain Conversation

Many real-world open-domain conversation applications have specific goal...
research
03/26/2018

On Chatbots Exhibiting Goal-Directed Autonomy in Dynamic Environments

Conversation interfaces (CIs), or chatbots, are a popular form of intell...
research
05/07/2022

Towards a Progression-Aware Autonomous Dialogue Agent

Recent advances in large-scale language modeling and generation have ena...
research
12/04/2018

Tartan: A retrieval-based socialbot powered by a dynamic finite-state machine architecture

This paper describes the Tartan conversational agent built for the 2018 ...
research
02/07/2022

Conversational Agents: Theory and Applications

In this chapter, we provide a review of conversational agents (CAs), dis...
research
01/31/2019

Exploring the context of recurrent neural network based conversational agents

Conversational agents have begun to rise both in the academic (in terms ...
research
04/17/2020

Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skills

Being engaging, knowledgeable, and empathetic are all desirable general ...

Please sign up or login with your details

Forgot password? Click here to reset