Benchmarks
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
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Greatest papers with code
MultiWOZ 2.1: A Consolidated Multi-Domain Dialogue Dataset with State Corrections and State Tracking Baselines
LREC 2020
• budzianowski/multiwoz
• 
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 #6 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.1
DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING
Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems
ACL 2019
• jasonwu0731/trade-dst
•
Over-dependence on domain ontology and lack of knowledge sharing across domains are two practical and yet less studied problems of dialogue state tracking.
Ranked #6 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.0
DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING TASK-ORIENTED DIALOGUE SYSTEMS TRANSFER LEARNING
Scalable Multi-Domain Dialogue State Tracking
We introduce a novel framework for state tracking which is independent of the slot value set, and represent the dialogue state as a distribution over a set of values of interest (candidate set) derived from the dialogue history or knowledge.
DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING TASK-ORIENTED DIALOGUE SYSTEMS TRANSFER LEARNING
Efficient Dialogue State Tracking by Selectively Overwriting Memory
This mechanism consists of two steps: (1) predicting state operation on each of the memory slots, and (2) overwriting the memory with new values, of which only a few are generated according to the predicted state operations.
Ranked #4 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.1
DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING
Non-Autoregressive Dialog State Tracking
ICLR 2020
• henryhungle/NADST
•
Recent efforts in Dialogue State Tracking (DST) for task-oriented dialogues have progressed toward open-vocabulary or generation-based approaches where the models can generate slot value candidates from the dialogue history itself.
Ranked #5 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.0
DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING
Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering
Multi-domain dialogue state tracking (DST) is a critical component for conversational AI systems.
DIALOGUE STATE TRACKING DOMAIN ADAPTATION MULTI-DOMAIN DIALOGUE STATE TRACKING QUESTION ANSWERING
Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking
We show that data augmentation through synthesized data can improve the accuracy of zero-shot learning for both the TRADE model and the BERT-based SUMBT model on the MultiWOZ 2. 1 dataset.
DATA AUGMENTATION DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING TRANSFER LEARNING ZERO-SHOT LEARNING
Parallel Interactive Networks for Multi-Domain Dialogue State Generation
EMNLP 2020
• BDBC-KG-NLP/PIN_EMNLP2020
•
In this study, we argue that the incorporation of these dependencies is crucial for the design of MDST and propose Parallel Interactive Networks (PIN) to model these dependencies.
DIALOGUE STATE TRACKING MULTI-DOMAIN DIALOGUE STATE TRACKING