RuCCoN: Clinical Concept Normalization in Russian

no code implementations • Findings (ACL) 2022 • Alexandr Nesterov, Galina Zubkova, Zulfat Miftahutdinov, Vladimir Kokh, Elena Tutubalina, Artem Shelmanov, Anton Alekseev, Manvel Avetisian, Andrey Chertok, Sergey Nikolenko

We present RuCCoN, a new dataset for clinical concept normalization in Russian manually annotated by medical professionals.

Startup success prediction and VC portfolio simulation using CrunchBase data

no code implementations • 27 Sep 2023 • Mark Potanin, Andrey Chertok, Konstantin Zorin, Cyril Shtabtsovsky

In summary, our work demonstrates the considerable promise of deep learning models and alternative unstructured data in predicting startup success and sets the stage for future advancements in this research area.

DetIE: Multilingual Open Information Extraction Inspired by Object Detection

1 code implementation • 24 Jun 2022 • Michael Vasilkovsky, Anton Alekseev, Valentin Malykh, Ilya Shenbin, Elena Tutubalina, Dmitriy Salikhov, Mikhail Stepnov, Andrey Chertok, Sergey Nikolenko

Our model sets the new state of the art performance of 67. 7% F1 on CaRB evaluated as OIE2016 while being 3. 35x faster at inference than previous state of the art.

Multilingual NLP Object +2

RuCLIP -- new models and experiments: a technical report

1 code implementation • 22 Feb 2022 • Alex Shonenkov, Andrey Kuznetsov, Denis Dimitrov, Tatyana Shavrina, Daniil Chesakov, Anastasia Maltseva, Alena Fenogenova, Igor Pavlov, Anton Emelyanov, Sergey Markov, Daria Bakshandaeva, Vera Shybaeva, Andrey Chertok

In the report we propose six new implementations of ruCLIP model trained on our 240M pairs.

Translation

Handwritten text generation and strikethrough characters augmentation

no code implementations • 14 Dec 2021 • Alex Shonenkov, Denis Karachev, Max Novopoltsev, Mark Potanin, Denis Dimitrov, Andrey Chertok

We introduce two data augmentation techniques, which, used with a Resnet-BiLSTM-CTC network, significantly reduce Word Error Rate (WER) and Character Error Rate (CER) beyond best-reported results on handwriting text recognition (HTR) tasks.

Data Augmentation HTR +1

Hybrid Graph Embedding Techniques in Estimated Time of Arrival Task

no code implementations • 8 Oct 2021 • Vadim Porvatov, Natalia Semenova, Andrey Chertok

Recently, deep learning has achieved promising results in the calculation of Estimated Time of Arrival (ETA), which is considered as predicting the travel time from the start point to a certain place along a given path.

Graph Embedding

RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark

2 code implementations • EMNLP 2020 • Tatiana Shavrina, Alena Fenogenova, Anton Emelyanov, Denis Shevelev, Ekaterina Artemova, Valentin Malykh, Vladislav Mikhailov, Maria Tikhonova, Andrey Chertok, Andrey Evlampiev

In this paper, we introduce an advanced Russian general language understanding evaluation benchmark -- RussianGLUE.

Common Sense Reasoning Lexical Entailment +5

Humans Keep It One Hundred: an Overview of AI Journey

1 code implementation • LREC 2020 • Tatiana Shavrina, Anton Emelyanov, Alena Fenogenova, Vadim Fomin, Vladislav Mikhailov, Andrey Evlampiev, Valentin Malykh, Vladimir Larin, Alex Natekin, Aleks Vatulin, R, Peter Romov, Daniil Anastasiev, Nikolai Zinov, Andrey Chertok

Artificial General Intelligence (AGI) is showing growing performance in numerous applications - beating human performance in Chess and Go, using knowledge bases and text sources to answer questions (SQuAD) and even pass human examination (Aristo project).

Text Generation

SberQuAD -- Russian Reading Comprehension Dataset: Description and Analysis

no code implementations • 20 Dec 2019 • Pavel Efimov, Andrey Chertok, Leonid Boytsov, Pavel Braslavski

SberQuAD -- a large scale analog of Stanford SQuAD in the Russian language - is a valuable resource that has not been properly presented to the scientific community.

Question Answering Reading Comprehension