Dialogue Management
24 papers with code • 0 benchmarks • 1 datasets
( Image credit: Bocklisch et al. )
Benchmarks
These leaderboards are used to track progress in Dialogue Management
DialoGLUE
Latest papers with no code
A Flexible Schema-Guided Dialogue Management Framework: From Friendly Peer to Virtual Standardized Cancer Patient
A schema-guided approach to dialogue management has been shown in recent work to be effective in creating robust customizable virtual agents capable of acting as friendly peers or task assistants.
Bootstrapping a User-Centered Task-Oriented Dialogue System
We present TacoBot, a task-oriented dialogue system built for the inaugural Alexa Prize TaskBot Challenge, which assists users in completing multi-step cooking and home improvement tasks.
A Mixture-of-Expert Approach to RL-based Dialogue Management
Despite recent advancements in language models (LMs), their application to dialogue management (DM) problems and ability to carry on rich conversations remain a challenge.
Dialogue Strategy Adaptation to New Action Sets Using Multi-dimensional Modelling
A major bottleneck for building statistical spoken dialogue systems for new domains and applications is the need for large amounts of training data.
A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-Oriented Dialogue Policy Learning
In this paper, we survey recent advances and challenges in dialogue policy from the prescriptive of RL.
Knowledge Graph is in Rescue: Task Oriented Dialogue System for Response Generation without NLU and DM
In this work, we build an end-to-end dialogue generation system that does not require NLU and DM components or their associated labels in the data.
Athena 2.0: Contextualized Dialogue Management for an Alexa Prize SocialBot
Athena 2. 0 is an Alexa Prize SocialBot that has been a finalist in the last two Alexa Prize Grand Challenges.
An Approach to Inference-Driven Dialogue Management within a Social Chatbot
In the third and final stage, our bot selects a small subset of predicates and translates them into an English response.
Findings from Experiments of On-line Joint Reinforcement Learning of Semantic Parser and Dialogue Manager with real Users
The analysis of these experiments gives us some insights, discussed in the paper, into the difficulty for the system's trainers to establish a coherent and constant behavioural strategy to enable a fast and good-quality training phase.
What Does The User Want? Information Gain for Hierarchical Dialogue Policy Optimisation
The dialogue management component of a task-oriented dialogue system is typically optimised via reinforcement learning (RL).
