2020

TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking

Heck, Michael, van Niekerk, Carel, Lubis, Nurul et al.

Understand

Task-oriented dialog systems rely on dialog state tracking (DST) to monitor the user's goal during the course of an interaction.

Multi-domain and open-vocabulary settings complicate the task considerably and demand scalable solutions.
In this paper we present a new approach to DST which makes use of various copy mechanisms to fill slots with values.
Our model has no need to maintain a list of candidate values.

Built on

Transferable multi-domain state generator for task-oriented dialogue systems
Original
Chien-Sheng Wu, Andrea Madotto, Ehsan Hosseini-Asl, Caiming Xiong, Richard Socher, and Pascale Fung. 2019 · 1905
Earlier work this paper cites.
BERT-DST: Scalable end-to-end dialogue state tracking with bidirectional encoder representations from transformer
Original
Guan-Lin Chao and Ian Lane. 2019 · 1907
Earlier work this paper cites.
MultiWOZ 2.1: Multi-domain dialogue state corrections and state tracking baselines
Original
Mihail Eric, Rahul Goel, Shachi Paul, Abhishek Sethi, Sanchit Agarwal, Shuyag Gao, and Dilek Hakkani-Tür. 2019 · 1907
Earlier work this paper cites.
SUMBT: Slot-utterance matching for universal and scalable belief tracking
Original
Hwaran Lee, Jinsik Lee, and Tae-Yoon Kim. 2019 · 1907
Earlier work this paper cites.
Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset
Original
Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, and Pranav Khaitan. 2019 · 1909
Earlier work this paper cites.
Find or classify? dual strategy for slot-value predictions on multi-domain dialog state tracking
Original
Jian-Guo Zhang, Kazuma Hashimoto, Chien-Sheng Wu, Yao Wan, Philip S Yu, Richard Socher, and Caiming Xiong. 2019 · 1910
Earlier work this paper cites.
Efficient dialogue state tracking by selectively overwriting memory
Original
Sungdong Kim, Sohee Yang, Gyuwan Kim, and Sang-Woo Lee. 2019 · 1911
Earlier work this paper cites.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
Earlier work this paper cites.
MA-DST: Multi-attention based scalable dialog state tracking
Original
Adarsh Kumar, Peter Ku, Anuj Kumar Goyal, Angeliki Metallinou, and Dilek Hakkani-Tür. 2020 · 2002
Earlier work this paper cites.
The hidden information state model: A practical framework for POMDP-based spoken dialogue management
Steve Young, Milica Gašić, Simon Keizer, François Mairesse, Jost Schatzmann, Blaise Thomson, and Kai Yu. 2010 · 2010
Earlier work this paper cites.

Similar

The second dialog state tracking challenge
Matthew Henderson, Blaise Thomson, and Jason D Williams. 2014 · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
Original
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Cited alongside, same era.
Targeted feature dropout for robust slot filling in natural language understanding
Puyang Xu and Ruhi Sarikaya. 2014 · 2014
Cited alongside, same era.
Neural belief tracker: Data-driven dialogue state tracking
Original
Nikola Mrkšić, Diarmuid O Séaghdha, Tsung-Hsien Wen, Blaise Thomson, and Steve Young. 2016 · 2016
Cited alongside, same era.
A network-based end-to-end trainable task-oriented dialogue system
Original
Tsung-Hsien Wen, David Vandyke, Nikola Mrkšić, Milica Gašić, Lina M Rojas-Barahona, Pei-Hao Su, Stefan Ultes, and Steve Young. 2016 · 2016
Cited alongside, same era.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Original
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al. 2016 · 2016
Cited alongside, same era.
An end-to-end trainable neural network model with belief tracking for task-oriented dialog
Original
Bing Liu and Ian Lane. 2017 · 2017
Cited alongside, same era.
Scalable multi-domain dialogue state tracking
Abhinav Rastogi, Dilek Hakkani-Tür, and Larry Heck. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
MultiWOZ - a large-scale multi-domain Wizard-of-Oz dataset for task-oriented dialogue modelling
Original
Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Inigo Casanueva, Stefan Ultes, Osman Ramadan, and Milica Gašić. 2018 · 2018
Cited alongside, same era.

Then

BERT: Pre-training of deep bidirectional transformers for language understanding
Original
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Later among the works it cites.
Toward scalable neural dialogue state tracking model
Original
Elnaz Nouri and Ehsan Hosseini-Asl. 2018 · 2018
Later among the works it cites.
Large-scale multi-domain belief tracking with knowledge sharing
Original
Osman Ramadan, Paweł Budzianowski, and Milica Gašić. 2018 · 2018
Later among the works it cites.
Multi-task learning for joint language understanding and dialogue state tracking
Abhinav Rastogi, Raghav Gupta, and Dilek Hakkani-Tur. 2018 · 2018
Later among the works it cites.
Towards universal dialogue state tracking
Liliang Ren, Kaige Xie, Lu Chen, and Kai Yu. 2018 · 2018
Later among the works it cites.
Building a conversational agent overnight with dialogue self-play
Original
Pararth Shah, Dilek Hakkani-Tür, Gokhan Tür, Abhinav Rastogi, Ankur Bapna, Neha Nayak, and Larry Heck. 2018 · 2018
Later among the works it cites.
An end-to-end approach for handling unknown slot values in dialogue state tracking
Original
Puyang Xu and Qi Hu. 2018 · 2018
Later among the works it cites.
Global-locally self-attentive dialogue state tracker
Original
Victor Zhong, Caiming Xiong, and Richard Socher. 2018 · 2018
Later among the works it cites.
Dialog state tracking: A neural reading comprehension approach
Shuyang Gao, Abhishek Sethi, Sanchit Agarwal, Tagyoung Chung, Dilek Hakkani-Tur, and Amazon Alexa AI. 2019 · 2019
Later among the works it cites.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Reading the bibliography…