Search Results for author: Mikhail Burtsev

Found 11 papers, 4 papers with code

Discourse-Driven Integrated Dialogue Development Environment for Open-Domain Dialogue Systems

no code implementations CODI 2021 Denis Kuznetsov, Dmitry Evseev, Lidia Ostyakova, Oleg Serikov, Daniel Kornev, Mikhail Burtsev

Development environments for spoken dialogue systems are popular today because they enable rapid creation of the dialogue systems in times when usage of the voice AI Assistants is constantly growing.

Spoken Dialogue Systems

Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questions

1 code implementation EMNLP 2021 Mohammad Aliannejadi, Julia Kiseleva, Aleksandr Chuklin, Jeffrey Dalton, Mikhail Burtsev

Enabling open-domain dialogue systems to ask clarifying questions when appropriate is an important direction for improving the quality of the system response.

Multi-Stream Transformers

no code implementations21 Jul 2021 Mikhail Burtsev, Anna Rumshisky

Transformer-based encoder-decoder models produce a fused token-wise representation after every encoder layer.

Short Text Clustering with Transformers

no code implementations31 Jan 2021 Leonid Pugachev, Mikhail Burtsev

Recent techniques for the task of short text clustering often rely on word embeddings as a transfer learning component.

Short Text Clustering Transfer Learning +1

Memory Representation in Transformer

no code implementations1 Jan 2021 Mikhail Burtsev, Yurii Kuratov, Anton Peganov, Grigory V. Sapunov

Adding trainable memory to selectively store local as well as global representations of a sequence is a promising direction to improve the Transformer model.

Language Modelling Machine Translation +1

Goal-Oriented Multi-Task BERT-Based Dialogue State Tracker

no code implementations5 Feb 2020 Pavel Gulyaev, Eugenia Elistratova, Vasily Konovalov, Yuri Kuratov, Leonid Pugachev, Mikhail Burtsev

The organizers introduced the Schema-Guided Dialogue (SGD) dataset with multi-domain conversations and released a zero-shot dialogue state tracking model.

Dialogue State Tracking Question Answering +1

Loss Landscape Sightseeing with Multi-Point Optimization

1 code implementation9 Oct 2019 Ivan Skorokhodov, Mikhail Burtsev

We present multi-point optimization: an optimization technique that allows to train several models simultaneously without the need to keep the parameters of each one individually.

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