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Found 10 papers, 4 papers with code
FBK’s Neural Machine Translation Systems for IWSLT 2016
They leverage linguistic information such as lemmas and part-of-speech tags of the source words in the form of additional factors along with the words.
Recent Neural Methods on Dialogue State Tracking for Task-Oriented Dialogue Systems: A Survey
This paper aims at providing a comprehensive overview of recent developments in dialogue state tracking (DST) for task-oriented conversational systems.
No that's not what I meant: Handling Third Position Repair in Conversational Question Answering
We demonstrate the usefulness of the data by training and evaluating strong baseline models for executing TPRs.
Domain-Aware Dialogue State Tracker for Multi-Domain Dialogue Systems
In task-oriented dialogue systems the dialogue state tracker (DST) component is responsible for predicting the state of the dialogue based on the dialogue history.
A Robust Data-Driven Approach for Dialogue State Tracking of Unseen Slot Values
This makes extending the candidate list for a slot without model retaining infeasible and also has limitations in modelling for low resource domains where training data for slot values are expensive.
Scalable Neural Dialogue State Tracking
A Dialogue State Tracker (DST) is a key component in a dialogue system aiming at estimating the beliefs of possible user goals at each dialogue turn.
Ranked #6 on
Dialogue State Tracking
on Wizard-of-Oz
Benchmarking machine learning models on multi-centre eICU critical care dataset
This is the first public benchmark on a multi-centre critical care dataset, comparing the performance of clinical gold standard with our predictive model.
Toward zero-shot Entity Recognition in Task-oriented Conversational Agents
We present a domain portable zero-shot learning approach for entity recognition in task-oriented conversational agents, which does not assume any annotated sentences at training time.
Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties [Extended Version]
In this work, we have developed a human-annotated dataset of 350 preference judgments among pairs of knowledge base properties for fixed entities.
