A survey on spoken language understanding: Recent advances and new frontiers
Spoken Language Understanding (SLU) aims to extract the semantics frame of user queries,
which is a core component in a task-oriented dialog system. With the burst of deep neural …
which is a core component in a task-oriented dialog system. With the burst of deep neural …
Generalized category discovery with decoupled prototypical network
Abstract Generalized Category Discovery (GCD) aims to recognize both known and novel
categories from a set of unlabeled data, based on another dataset labeled with only known …
categories from a set of unlabeled data, based on another dataset labeled with only known …
New intent discovery with pre-training and contrastive learning
New intent discovery aims to uncover novel intent categories from user utterances to expand
the set of supported intent classes. It is a critical task for the development and service …
the set of supported intent classes. It is a critical task for the development and service …
Clusterllm: Large language models as a guide for text clustering
We introduce ClusterLLM, a novel text clustering framework that leverages feedback from an
instruction-tuned large language model, such as ChatGPT. Compared with traditional …
instruction-tuned large language model, such as ChatGPT. Compared with traditional …
Understanding user intent modeling for conversational recommender systems: a systematic literature review
User intent modeling in natural language processing deciphers user requests to allow for
personalized responses. The substantial volume of research (exceeding 13,000 …
personalized responses. The substantial volume of research (exceeding 13,000 …
Proactive conversational agents
Conversational agents, or commonly known as dialogue systems, have gained escalating
popularity in recent years. Their widespread applications support conversational interactions …
popularity in recent years. Their widespread applications support conversational interactions …
Transfer and alignment network for generalized category discovery
Generalized Category Discovery (GCD) is a crucial real-world task that aims to recognize
both known and novel categories from an unlabeled dataset by leveraging another labeled …
both known and novel categories from an unlabeled dataset by leveraging another labeled …
Point-gcc: Universal self-supervised 3d scene pre-training via geometry-color contrast
Geometry and color information provided by the point clouds are both crucial for 3D scene
understanding. Two pieces of information characterize the different aspects of point clouds …
understanding. Two pieces of information characterize the different aspects of point clouds …
Synergizing large language models and pre-trained smaller models for conversational intent discovery
Abstract In Conversational Intent Discovery (CID), Small Language Models (SLMs) struggle
with overfitting to familiar intents and fail to label newly discovered ones. This issue stems …
with overfitting to familiar intents and fail to label newly discovered ones. This issue stems …
A probabilistic framework for discovering new intents
Discovering new intents is of great significance for establishing the Task-Oriented Dialogue
System. Most existing methods either cannot transfer prior knowledge contained in known …
System. Most existing methods either cannot transfer prior knowledge contained in known …