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A review of dialogue systems: current trends and future directions
Advances in dialogue systems have recently been made in various fields as an easy to use and inexpensive option to support or replace workers....
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Measuring perceived empathy in dialogue systems
Dialogue systems, from Virtual Personal Assistants such as Siri, Cortana, and Alexa to state-of-the-art systems such as BlenderBot3 and ChatGPT, are...
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Linguistics-based dialogue simulations to evaluate argumentative conversational recommender systems
Conversational recommender systems aim at recommending the most relevant information for users based on textual or spoken dialogues, through which...
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Personality Enhanced Emotion Generation Modeling for Dialogue Systems
Emotion plays a crucial role in human communication, as it adds depth and richness to conversations. In recent years, there has been growing interest...
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EVA2.0: Investigating Open-domain Chinese Dialogue Systems with Large-scale Pre-training
Large-scale pre-training has shown remarkable performance in building open-domain dialogue systems. However, previous works mainly focus on showing...
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Recent advances in deep learning based dialogue systems: a systematic survey
Dialogue systems are a popular natural language processing (NLP) task as it is promising in real-life applications. It is also a complicated task...
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Unsupervised Dialogue State Tracking for End-to-End Task-Oriented Dialogue with a Multi-Span Prediction Network
This paper focuses on end-to-end task-oriented dialogue systems, which jointly handle dialogue state tracking (DST) and response generation....
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Sequential or jum**: context-adaptive response generation for open-domain dialogue systems
Neural response generation can automatically produce replies for open-domain dialogue systems without hand-crafted rules or templates. Current...
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Continual Learning for Task-Oriented Dialogue Systems
Task-oriented Dialogue Systems (ToDS) are widely popular now-a-days due to their pervasive usage in real-world applications like fight booking,...
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Dialogue Specific Pre-training Tasks for Improved Dialogue State Tracking
Although Pre-trained language models are widely used in dialogue state tracking, there exists little work on pre-training tasks that are designed for...
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DialGNN: Heterogeneous Graph Neural Networks for Dialogue Classification
Dialogue systems have attracted growing research interests due to its widespread applications in various domains. However, most research work focus...
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Exploring implicit persona knowledge for personalized dialogue generation
In recent years, personalized dialogue systems have drawn growing attention as they can serve as a personalized assistant for a specific user. A key...
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Lifelong and Continual Learning Dialogue Systems
This book introduces the new paradigm of lifelong and continual learning dialogue systems to endow dialogue systems with the ability to learn...
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Mutual character dialogue generation with semi-supervised multitask learners and awareness
Consistent efforts have been ongoing to improve the friendliness and reliability of informal dialogue systems. However, most research focuses solely...
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Revisiting clustering for efficient unsupervised dialogue structure induction
In the development of a task-oriented dialogue system, defining the dialogue structure is a time-consuming task. Hence, several works have looked...
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Dialogue Explanations for Rule-Based AI Systems
The need for AI systems to explain themselves is increasingly recognised as a priority, particularly in domains where incorrect decisions can result...
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MODE: a multimodal open-domain dialogue dataset with explanation
The need for high-quality data has been a key issue hindering the research of dialogue tasks. Recent studies try to build datasets through manual,...
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Interpreting open-domain dialogue generation by disentangling latent feature representations
Currently end-to-end deep learning based open-domain dialogue systems remain black box models, making it easy to generate irrelevant contents with...
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A Unified Framework for Slot based Response Generation in a Multimodal Dialogue System
Natural Language Understanding (NLU) and Natural Language Generation (NLG) are the two critical components of every conversational system that...
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Efficient slot correlation learning network for multi-domain dialogue state tracking
Task-oriented dialogue systems depend on dialogue state tracking to keep track of the intentions of users in the course of conversations. Recent...
