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Found 7 papers, 2 papers with code
Improving Top-K Decoding for Non-Autoregressive Semantic Parsing via Intent Conditioning
As the top-level intent largely governs the syntax and semantics of a parse, the intent conditioning allows the model to better control beam search and improves the quality and diversity of top-k outputs.
TableFormer: Robust Transformer Modeling for Table-Text Encoding
Existing models for table understanding require linearization of the table structure, where row or column order is encoded as an unwanted bias.
Alexa Conversations: An Extensible Data-driven Approach for Building Task-oriented Dialogue Systems
Finally, we evaluate our system using a typical movie ticket booking task and show that the dialogue simulator is an essential component of the system that leads to over $50\%$ improvement in turn-level action signature prediction accuracy.
Towards Universal Dialogue Act Tagging for Task-Oriented Dialogues
In unsupervised learning experiments we achieve an F1 score of 54. 1% on system turns in human-human dialogues.
MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines
To fix the noisy state annotations, we use crowdsourced workers to re-annotate state and utterances based on the original utterances in the dataset.
Ranked #16 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.0
Dialogue State Tracking
Multi-domain Dialogue State Tracking
HyST: A Hybrid Approach for Flexible and Accurate Dialogue State Tracking
In this work, we analyze the performance of these two alternative dialogue state tracking methods, and present a hybrid approach (HyST) which learns the appropriate method for each slot type.
Ranked #18 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.0
Dialogue State Tracking
Multi-domain Dialogue State Tracking
Flexible and Scalable State Tracking Framework for Goal-Oriented Dialogue Systems
This limits such systems in two different ways: If there is an update in the task domain, the dialogue system usually needs to be updated or completely re-trained.
