Papers by Vladimir Ivanov
Cross-Modal Conceptualization in Bottleneck Models (2023.emnlp-main)
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Danis Alukaev, Semen Kiselev, Ilya Pershin, Bulat Ibragimov, Vladimir Ivanov, Alexey Kornaev, Ivan Titov
| Challenge: | Existing models that use text descriptions to predict labels are limited in their interpretations. |
| Approach: | They propose to use text descriptions to guide the induction of concepts in CBMs . they propose to employ a more moderate assumption and instead use text to guide induction . |
| Outcome: | The proposed model adopts a more moderate assumption and uses text descriptions to guide the induction of concepts. |
Medical Crossing: a Cross-lingual Evaluation of Clinical Entity Linking (2022.lrec-1)
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Anton Alekseev, Zulfat Miftahutdinov, Elena Tutubalina, Artem Shelmanov, Vladimir Ivanov, Vladimir Kokh, Alexander Nesterov, Manvel Avetisian, Andrei Chertok, Sergey Nikolenko
| Challenge: | Existing approaches to medical entity linking are limited in terms of data volume and languages. |
| Approach: | They propose to use clinical reports, clinical guidelines, and medical research papers to evaluate cross-lingual medical entity linking. |
| Outcome: | The proposed model outperforms existing models on clinical reports, clinical guidelines, and medical research papers. |
Entity Linking over Nested Named Entities for Russian (2022.lrec-1)
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Natalia Loukachevitch, Pavel Braslavski, Vladimir Ivanov, Tatiana Batura, Suresh Manandhar, Artem Shelmanov, Elena Tutubalina
| Challenge: | Entity linking is a popular NLP task, where a system needs to link a named entity to a concept in a knowledge base such as Wikidata. |
| Approach: | They describe the main design principles behind entity linking annotation in the recently released Russian NEREL dataset for information extraction. |
| Outcome: | The NEREL dataset is the largest Russian dataset annotated with entities and relations. |