55 citations · 151 across the 25 of their papers we have counts for
8 papers · 1 filter
Semi-supervised Bootstrapping of Dialogue State Trackers for Task Oriented Modelling
Bo-Hsiang Tseng, Marek Rei, Paweł Budzianowski +3
Dialogue systems benefit greatly from optimizing on detailed annotations, such as transcribed utterances, internal dialogue state representations and dialogue act labels. However,…
Tree-Structured Semantic Encoder with Knowledge Sharing for Domain Adaptation in Natural Language Generation
Bo-Hsiang Tseng, Paweł Budzianowski, Yen-Chen Wu +1
Domain adaptation in natural language generation (NLG) remains challenging because of the high complexity of input semantics across domains and limited data of a target domain. Thi…
Domain Transfer in Dialogue Systems without Turn-Level Supervision
Joachim Bingel, Victor Petrén Bach Hansen, Ana Valeria Gonzalez +3
Task oriented dialogue systems rely heavily on specialized dialogue state tracking (DST) modules for dynamically predicting user intent throughout the conversation. State-of-the-ar…
PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking
Matthew Henderson, Ivan Vulić, Iñigo Casanueva +7
We present PolyResponse, a conversational search engine that supports task-oriented dialogue. It is a retrieval-based approach that bypasses the complex multi-component design of t…
Hello, It's GPT-2 -- How Can I Help You? Towards the Use of Pretrained Language Models for Task-Oriented Dialogue Systems
Paweł Budzianowski, Ivan Vulić
Data scarcity is a long-standing and crucial challenge that hinders quick development of task-oriented dialogue systems across multiple domains: task-oriented dialogue models are e…
Training Neural Response Selection for Task-Oriented Dialogue Systems
Matthew Henderson, Ivan Vulić, Daniela Gerz +7
Despite their popularity in the chatbot literature, retrieval-based models have had modest impact on task-oriented dialogue systems, with the main obstacle to their application bei…
A Repository of Conversational Datasets
Matthew Henderson, Paweł Budzianowski, Iñigo Casanueva +8
Progress in Machine Learning is often driven by the availability of large datasets, and consistent evaluation metrics for comparing modeling approaches. To this end, we present a r…
Addressing Objects and Their Relations: The Conversational Entity Dialogue Model
Stefan Ultes, Paweł Budzianowski, Iñigo Casanueva +5
Statistical spoken dialogue systems usually rely on a single- or multi-domain dialogue model that is restricted in its capabilities of modelling complex dialogue structures, e.g.,…