1 citations · 1 across the 6 of their papers we have counts for
7 papers
Data filtering methods for training language models
Egor Shevchenko, Elena Bruches
Data quality is a critical factor in the effectiveness of machine learning models. Label errors, present even in widely used benchmarks, introduce noise into training data and redu…
AINL-Eval 2025 Shared Task: Detection of AI-Generated Scientific Abstracts in Russian
Tatiana Batura, Elena Bruches, Milana Shvenk +1
The rapid advancement of large language models (LLMs) has revolutionized text generation, making it increasingly difficult to distinguish between human- and AI-generated content. T…
Russian-Language Multimodal Dataset for Automatic Summarization of Scientific Papers
Alena Tsanda, Elena Bruches
The paper discusses the creation of a multimodal dataset of Russian-language scientific papers and testing of existing language models for the task of automatic text summarization.…
Automatic Aspect Extraction from Scientific Texts
Anna Marshalova, Elena Bruches, Tatiana Batura
Being able to extract from scientific papers their main points, key insights, and other important information, referred to here as aspects, might facilitate the process of conducti…
TERMinator: A system for scientific texts processing
Elena Bruches, Olga Tikhobaeva, Yana Dementyeva +1
This paper is devoted to the extraction of entities and semantic relations between them from scientific texts, where we consider scientific terms as entities. In this paper, we pre…
A system for information extraction from scientific texts in Russian
Elena Bruches, Anastasia Mezentseva, Tatiana Batura
In this paper, we present a system for information extraction from scientific texts in the Russian language. The system performs several tasks in an end-to-end manner: term recogni…
Entity Recognition and Relation Extraction from Scientific and Technical Texts in Russian
Elena Bruches, Alexey Pauls, Tatiana Batura +1
This paper is devoted to the study of methods for information extraction (entity recognition and relation classification) from scientific texts on information technology. Scientifi…