activity
20172020
most citedRasa: Open Source Language Understanding and Dialogue Management

139 citations · 256 across the 3 of their papers we have counts for

collaborators
Showing cs.CLShow all

5 papers · 1 filter

cs.CL2020113 cited

DIET: Lightweight Language Understanding for Dialogue Systems

Tanja Bunk, Daksh Varshneya, Vladimir Vlasov +1

Large-scale pre-trained language models have shown impressive results on language understanding benchmarks like GLUE and SuperGLUE, improving considerably over other pre-training m…

cs.CL20204 cited

Where is the context? -- A critique of recent dialogue datasets

Johannes E. M. Mosig, Vladimir Vlasov, Alan Nichol

Recent dialogue datasets like MultiWOZ 2.1 and Taskmaster-1 constitute some of the most challenging tasks for present-day dialogue models and, therefore, are widely used for system…

cs.CL2019

Dialogue Transformers

Vladimir Vlasov, Johannes E. M. Mosig, Alan Nichol

We introduce a dialogue policy based on a transformer architecture, where the self-attention mechanism operates over the sequence of dialogue turns. Recent work has used hierarchic…

cs.CL2018

Few-Shot Generalization Across Dialogue Tasks

Vladimir Vlasov, Akela Drissner-Schmid, Alan Nichol

Machine-learning based dialogue managers are able to learn complex behaviors in order to complete a task, but it is not straightforward to extend their capabilities to new domains.…

cs.CL2017139 cited

Rasa: Open Source Language Understanding and Dialogue Management

Tom Bocklisch, Joey Faulkner, Nick Pawlowski +1

We introduce a pair of tools, Rasa NLU and Rasa Core, which are open source python libraries for building conversational software. Their purpose is to make machine-learning based d…