Papers by Galina Zubkova
MADD: Multi-Agent Drug Discovery Orchestra (2025.findings-emnlp)
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Gleb Vitalevich Solovev, Alina Borisovna Zhidkovskaya, Anastasia Orlova, Nina Gubina, Anastasia Vepreva, Rodion Golovinskii, Ilya Tonkii, Ivan Dubrovsky, Ivan Gurev, Dmitry Gilemkhanov, Denis Chistiakov, Timur A. Aliev, Ivan Poddiakov, Galina Zubkova, Ekaterina V. Skorb, Vladimir Vinogradov, Alexander Boukhanovsky, Nikolay Nikitin, Andrei Dmitrenko, Anna Kalyuzhnaya, Andrey Savchenko
| Challenge: | Recent advances in artificial intelligence have limited access to wet-lab tools for hit identification . multi-agent systems combine interpretability of LLMs with precision of specialized models and tools . |
| Approach: | They propose a multi-agent system that builds and executes customized hit identification pipelines from natural language queries. |
| Outcome: | The proposed system reduces the complexity of traditional screening methods and improves efficiency. |
RuCCoD: Towards Automated ICD Coding in Russian (2025.emnlp-main)
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Alexandr Nesterov, Andrey Sakhovskiy, Ivan Sviridov, Airat Valiev, Vladimir Makharev, Petr Anokhin, Galina Zubkova, Elena Tutubalina
| Challenge: | a new dataset for clinical coding in Russian is available for download . human coders must navigate a wide array of medical terminology and time pressures . |
| Approach: | They present a new dataset for ICD coding in Russian, a language with limited biomedical resources. |
| Outcome: | The proposed model improves accuracy on an in-house EHR dataset from 2017 to 2021. |
3MDBench: Medical Multimodal Multi-agent Dialogue Benchmark (2025.emnlp-main)
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Ivan Sviridov, Amina Miftakhova, Tereshchenko Artemiy Vladimirovich, Galina Zubkova, Pavel Blinov, Andrey Savchenko
| Challenge: | Large Vision-Language Models (LVLMs) are being explored in medicine but their ability to conduct complex real-world telemedicine consultations remains underexplored. |
| Approach: | They propose to use large vision-language models to conduct telemedicine consultations using a framework that simulates patient variability and evaluates diagnostic accuracy and dialogue quality via Assessor Agent. |
| Outcome: | The proposed framework compares diagnostic strategies for open and closed-source LVLMs and shows that multimodal dialogue improves F1 score by 6.5% over non-dialogue settings. |
RuCCoN: Clinical Concept Normalization in Russian (2022.findings-acl)
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Alexandr Nesterov, Galina Zubkova, Zulfat Miftahutdinov, Vladimir Kokh, Elena Tutubalina, Artem Shelmanov, Anton Alekseev, Manvel Avetisian, Andrey Chertok, Sergey Nikolenko
| Challenge: | a new dataset for clinical concept normalization in Russian is available for download . ehrs contains over 16,028 entity mentions manually linked to over 2,409 unique concepts . |
| Approach: | They present a dataset for clinical concept normalization in Russian manually annotated by medical professionals. |
| Outcome: | The proposed dataset contains 16,028 entity mentions manually linked to over 2,409 unique concepts from the Russian language part of the UMLS ontology. |