Hierarchical reinforcement learning with guidance for multi-domain dialogue policy
Achieving high performance in a multi-domain dialogue system with low computation is
undoubtedly challenging. Previous works applying an end-to-end approach have been very …
undoubtedly challenging. Previous works applying an end-to-end approach have been very …
Corrective guidance and learning for dialogue management
Establishing robust dialogue policy with low computation cost is challenging, especially for
multi-domain task-oriented dialogue management due to the high complexity in state and …
multi-domain task-oriented dialogue management due to the high complexity in state and …
Hyknow: End-to-end task-oriented dialog modeling with hybrid knowledge management
Task-oriented dialog (TOD) systems typically manage structured knowledge (eg ontologies
and databases) to guide the goal-oriented conversations. However, they fall short of …
and databases) to guide the goal-oriented conversations. However, they fall short of …
Opera: Harmonizing task-oriented dialogs and information seeking experience
Existing studies in conversational AI mostly treat task-oriented dialog (TOD) and question
answering (QA) as separate tasks. Towards the goal of constructing a conversational agent …
answering (QA) as separate tasks. Towards the goal of constructing a conversational agent …
Injecting Comparison Skills in Task-Oriented Dialogue Systems for Database Search Results Disambiguation
In task-oriented dialogue (TOD) systems designed to aid users accomplish specific goals in
one or more domains, the agent retrieves entities that satisfy user constraints from the …
one or more domains, the agent retrieves entities that satisfy user constraints from the …
End-to-end task-oriented dialog modeling with semi-structured knowledge management
Current task-oriented dialog (TOD) systems mostly manage structured knowledge (eg
databases and tables) to guide the goal-oriented conversations. However, they fall short of …
databases and tables) to guide the goal-oriented conversations. However, they fall short of …
[HTML][HTML] Enhancing Task-Oriented Dialogue Modeling through Coreference-Enhanced Contrastive Pre-Training
Y Huang, S Chen, Y Chen, J Feng, C Deng - Applied Sciences, 2024 - mdpi.com
Pre-trained language models (PLMs) are proficient at understanding context in plain text but
often struggle with the nuanced linguistics of task-oriented dialogues. The information …
often struggle with the nuanced linguistics of task-oriented dialogues. The information …
MT-DST: Multi-Task Strategy for Few-shot Dialog State Tracking
J Tang - 2023 5th International Conference on Machine …, 2023 - ieeexplore.ieee.org
The remarkable effectiveness of large pre-trained models in Task-Oriented Dialogue (TOD)
systems, particularly in the area of Dialog State Tracking (DST), has been well documented …
systems, particularly in the area of Dialog State Tracking (DST), has been well documented …