Interactive natural language processing
Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within
the field of NLP, aimed at addressing limitations in existing frameworks while aligning with …
the field of NLP, aimed at addressing limitations in existing frameworks while aligning with …
A cooperative memory network for personalized task-oriented dialogue systems with incomplete user profiles
There is increasing interest in developing personalized Task-oriented Dialogue Systems
(TDSs). Previous work on personalized TDSs often assumes that complete user profiles are …
(TDSs). Previous work on personalized TDSs often assumes that complete user profiles are …
Learning low-resource end-to-end goal-oriented dialog for fast and reliable system deployment
Existing end-to-end dialog systems perform less effectively when data is scarce. To obtain
an acceptable success in real-life online services with only a handful of training examples …
an acceptable success in real-life online services with only a handful of training examples …
[HTML][HTML] An ecosystem for personal knowledge graphs: A survey and research roadmap
This paper presents an ecosystem for personal knowledge graphs (PKGs), commonly
defined as resources of structured information about entities related to an individual, their …
defined as resources of structured information about entities related to an individual, their …
[图书][B] Extracting and inferring personal attributes from dialogue
Z Wang - 2021 - search.proquest.com
Personal attributes represent structured information about a person, such as their hobbies,
pets, family, likes and dislikes. In this work, we introduce the tasks of extracting and inferring …
pets, family, likes and dislikes. In this work, we introduce the tasks of extracting and inferring …
DialAug: Mixing up dialogue contexts in contrastive learning for robust conversational modeling
L Poddar, P Wang, J Reinspach - arXiv preprint arXiv:2204.07679, 2022 - arxiv.org
Retrieval-based conversational systems learn to rank response candidates for a given
dialogue context by computing the similarity between their vector representations. However …
dialogue context by computing the similarity between their vector representations. However …
From easy to hard: Improving personalized response generation of task-oriented dialogue systems by leveraging capacity in open-domain dialogues
M Zhao, L Wang, Z Jiang, Y Liu, R Li, Z Hu… - Knowledge-Based Systems, 2024 - Elsevier
A task-oriented dialogue system (TOD) is an important application of artificial intelligence. In
the past few years, works on personalized TODs have attracted increased research attention …
the past few years, works on personalized TODs have attracted increased research attention …
CS-BERT: a pretrained model for customer service dialogues
P Wang, J Fang, J Reinspach - … of the 3rd Workshop on Natural …, 2021 - aclanthology.org
Large-scale pretrained transformer models have demonstrated state-of-the-art (SOTA)
performance in a variety of NLP tasks. Nowadays, numerous pretrained models are …
performance in a variety of NLP tasks. Nowadays, numerous pretrained models are …
[PDF][PDF] Optimizing dialog policy with large action spaces using deep reinforcement learning
Dialogue policy is responsible to select the next appropriate action from the current dialogue
state to accomplish the user goal efficiently. Present commercial task-oriented dialogue …
state to accomplish the user goal efficiently. Present commercial task-oriented dialogue …
Multi-modal emotion recognition for user adaptation in social robots
M Schiffmann, A Thoma, A Richert - International Conference on Applied …, 2021 - Springer
The interaction of humans and robots in everyday contexts is no longer a vision of the future.
This is demonstrated, for example, in the increasing use of service robots, eg, household …
This is demonstrated, for example, in the increasing use of service robots, eg, household …