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Found 13 papers, 8 papers with code
Disentangled Knowledge Transfer for OOD Intent Discovery with Unified Contrastive Learning
Discovering Out-of-Domain(OOD) intents is essential for developing new skills in a task-oriented dialogue system.
Task-Oriented Clustering for Dialogues
A reliable clustering algorithm for task-oriented dialogues can help developer analysis and define dialogue tasks efficiently.
Revisit Overconfidence for OOD Detection: Reassigned Contrastive Learning with Adaptive Class-dependent Threshold
Detecting Out-of-Domain (OOD) or unknown intents from user queries is essential in a task-oriented dialog system.
Domain-Oriented Prefix-Tuning: Towards Efficient and Generalizable Fine-tuning for Zero-Shot Dialogue Summarization
The most advanced abstractive dialogue summarizers lack generalization ability on new domains and the existing researches for domain adaptation in summarization generally rely on large-scale pre-trainings.
Co-VQA : Answering by Interactive Sub Question Sequence
Most existing approaches to Visual Question Answering (VQA) answer questions directly, however, people usually decompose a complex question into a sequence of simple sub questions and finally obtain the answer to the original question after answering the sub question sequence(SQS).
TODSum: Task-Oriented Dialogue Summarization with State Tracking
Previous dialogue summarization datasets mainly focus on open-domain chitchat dialogues, while summarization datasets for the broadly used task-oriented dialogue haven't been explored yet.
Capturing Event Argument Interaction via A Bi-Directional Entity-Level Recurrent Decoder
Capturing interactions among event arguments is an essential step towards robust event argument extraction (EAE).
Modeling Discriminative Representations for Out-of-Domain Detection with Supervised Contrastive Learning
Detecting Out-of-Domain (OOD) or unknown intents from user queries is essential in a task-oriented dialog system.
Novel Slot Detection: A Benchmark for Discovering Unknown Slot Types in the Task-Oriented Dialogue System
Existing slot filling models can only recognize pre-defined in-domain slot types from a limited slot set.
Converse, Focus and Guess -- Towards Multi-Document Driven Dialogue
We propose a novel task, Multi-Document Driven Dialogue (MD3), in which an agent can guess the target document that the user is interested in by leading a dialogue.
Syntactic Graph Convolutional Network for Spoken Language Understanding
Slot filling and intent detection are two major tasks for spoken language understanding.
Answer-Driven Visual State Estimator for Goal-Oriented Visual Dialogue
In this paper, we propose an Answer-Driven Visual State Estimator (ADVSE) to impose the effects of different answers on visual states.
