activity
20182023
most citedDIET: Lightweight Language Understanding for Dialogue Systems

113 citations · 119 across the 3 of their papers we have counts for

collaborators

5 papers

cs.IR20232 cited

UNICON: A unified framework for behavior-based consumer segmentation in e-commerce

Manuel Dibak, Vladimir Vlasov, Nour Karessli +5

Data-driven personalization is a key practice in fashion e-commerce, improving the way businesses serve their consumers needs with more relevant content. While hyper-personalizatio…

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.…