" Do you follow me?": A Survey of Recent Approaches in Dialogue State Tracking
While communicating with a user, a task-oriented dialogue system has to track the user's
needs at each turn according to the conversation history. This process called dialogue state …
needs at each turn according to the conversation history. This process called dialogue state …
Dynamic dialogue policy for continual reinforcement learning
Continual learning is one of the key components of human learning and a necessary
requirement of artificial intelligence. As dialogue can potentially span infinitely many topics …
requirement of artificial intelligence. As dialogue can potentially span infinitely many topics …
Infusing emotions into task-oriented dialogue systems: Understanding, management, and generation
Emotions are indispensable in human communication, but are often overlooked in task-
oriented dialogue (ToD) modelling, where the task success is the primary focus. While …
oriented dialogue (ToD) modelling, where the task success is the primary focus. While …
Confidence estimation for llm-based dialogue state tracking
Estimation of a model's confidence on its outputs is critical for Conversational AI systems
based on large language models (LLMs), especially for reducing hallucination and …
based on large language models (LLMs), especially for reducing hallucination and …
From Chatter to Matter: Addressing Critical Steps of Emotion Recognition Learning in Task-oriented Dialogue
Emotion recognition in conversations (ERC) is a crucial task for building human-like
conversational agents. While substantial efforts have been devoted to ERC for chit-chat …
conversational agents. While substantial efforts have been devoted to ERC for chit-chat …
[PDF][PDF] User simulation in task-oriented dialog systems based on large language models via in-context learning
R Horst - 2024 - fbmn.h-da.de
The growing importance of human-computer interaction and natural language processing is
highlighted by significant advances such as the introduction of ChatGPT, a Large Language …
highlighted by significant advances such as the introduction of ChatGPT, a Large Language …
CAMELL: Confidence-based Acquisition Model for Efficient Self-supervised Active Learning with Label Validation
Supervised neural approaches are hindered by their dependence on large, meticulously
annotated datasets, a requirement that is particularly cumbersome for sequential tasks. The …
annotated datasets, a requirement that is particularly cumbersome for sequential tasks. The …
Ontology Construction for Task-oriented Dialogue
R Vukovic - Proceedings of the 20th Workshop of Young …, 2024 - aclanthology.org
Ontology Construction for Task-oriented Dialogue Page 1 The 20th Annual Meeting of the
Young Researchers’ Roundtable on Spoken Dialogue Systems, pages 53–56 September …
Young Researchers’ Roundtable on Spoken Dialogue Systems, pages 53–56 September …
Span-prediction of Unknown Values for Long-sequence Dialogue State Tracking
Dialogue state tracking is one of the main components in task-oriented dialogue systems
whose duty is to track the user's goal during the conversation. Due to the diversity in natural …
whose duty is to track the user's goal during the conversation. Due to the diversity in natural …
Towards Emotion-aware Task-oriented Dialogue Systems in the Era of Large Language Models
S Feng - Proceedings of the 20th Workshop of Young …, 2024 - aclanthology.org
My research interests lie in the area of modelling affective behaviours of interlocutors in
conversations. In particular, I look at emotion perception, expression, and management in …
conversations. In particular, I look at emotion perception, expression, and management in …