Manvel Avetisian — accepted AI-conference papers

2022

RuCCoN: Clinical Concept Normalization in Russian

Alexandr Nesterov, Galina Zubkova, Zulfat Miftahutdinov, Vladimir Kokh, Elena Tutubalina, Artem Shelmanov +4

ACL 2022findings

We present RuCCoN, a new dataset for clinical concept normalization in Russian manually annotated by medical professionals. It contains over 16,028 entity mentions manually linked to over 2,409 unique concepts from the Russian language part of the UMLS ontology. We provide train/test splits for diff…

Cited by 7 Source ↗PDF ↗code ↗Scholar ↗

2022

Towards Computationally Feasible Deep Active Learning

Akim Tsvigun, Artem Shelmanov, Gleb Kuzmin, Leonid Sanochkin, Daniil Larionov, Gleb Gusev +2

NAACL 2022findings

Active learning (AL) is a prominent technique for reducing the annotation effort required for training machine learning models. Deep learning offers a solution for several essential obstacles to deploying AL in practice but introduces many others. One of such problems is the excessive computational…

Cited by 21 Source ↗PDF ↗code ↗Scholar ↗

2022

Uncertainty Estimation of Transformer Predictions for Misclassification Detection

Artem Vazhentsev, Gleb Kuzmin, Artem Shelmanov, Akim Tsvigun, Evgenii Tsymbalov, Kirill Fedyanin +6

ACL 2022long

Uncertainty estimation (UE) of model predictions is a crucial step for a variety of tasks such as active learning, misclassification detection, adversarial attack detection, out-of-distribution detection, etc. Most of the works on modeling the uncertainty of deep neural networks evaluate these metho…

Cited by 49 Source ↗PDF ↗code ↗Scholar ↗