45 citations · 46 across the 13 of their papers we have counts for
14 papers
ToolHACE: A Dataset for Detecting Hallucinations in Tool-Based LLM Responses
Nikolay Ivanov, Sergey Pletenev, Elisei Rykov +8
Tool-augmented language models ground their responses in external tool outputs, improving reliability beyond parametric knowledge alone. However, even when the correct tool is call…
MemToC: Benchmarking Memory-Tool Conflict Resolution in Large Language Models
Arseniy Varlamov, Rishat Zinnatullin, Elisei Rykov +2
Tool-augmented LLMs must arbitrate between two fallible sources when a tool return conflicts with their parametric memory, yet existing evaluations measure source preference withou…
PluraMath: Extending Mathematical Reasoning Evaluation Beyond High-Resource Languages
Daryna Dementieva, Nikolay Babakov, Kathy Hämmerl +14
Mathematical reasoning has become a central task for evaluating and tuning reasoning Large Language Models (LLMs), yet existing benchmarks remain heavily biased toward high-resourc…
The Tatoxa System for Text Detoxification in Low-Resource Languages: The Case of Tatar
Ilseyar Alimova, Bogdan Monogov, Artyom Mazur +5
Text detoxification, the automated detection and mitigation of abusive and harmful content, is essential for ensuring the safety of online communities and protecting users. However…
SemEval-2026 Task 3: Dimensional Aspect-Based Sentiment Analysis (DimABSA)
Liang-Chih Yu, Jonas Becker, Shamsuddeen Hassan Muhammad +14
We present the SemEval-2026 shared task on Dimensional Aspect-Based Sentiment Analysis (DimABSA), which improves traditional ABSA by modeling sentiment along valence-arousal (VA) d…
DimABSA: Building Multilingual and Multidomain Datasets for Dimensional Aspect-Based Sentiment Analysis
Lung-Hao Lee, Liang-Chih Yu, Natalia Loukashevich +13
Aspect-Based Sentiment Analysis (ABSA) focuses on extracting sentiment at a fine-grained aspect level and has been widely applied across real-world domains. However, existing ABSA…
Multimodal Evaluation of Russian-language Architectures
Artem Chervyakov, Ulyana Isaeva, Anton Emelyanov +15
Multimodal large language models (MLLMs) are currently at the center of research attention, showing rapid progress in scale and capabilities, yet their intelligence, limitations, a…
Targeted Test Selection Approach in Continuous Integration
Pavel Plyusnin, Aleksey Antonov, Vasilii Ermakov +4
In modern software development change-based testing plays a crucial role. However, as codebases expand and test suites grow, efficiently managing the testing process becomes increa…
MERA Code: A Unified Framework for Evaluating Code Generation Across Tasks
Artem Chervyakov, Alexander Kharitonov, Pavel Zadorozhny +20
Advancements in LLMs have enhanced task automation in software engineering; however, current evaluations primarily focus on natural language tasks, overlooking code quality. Most b…
BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages
Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin +45
People worldwide use language in subtle and complex ways to express emotions. Although emotion recognition--an umbrella term for several NLP tasks--impacts various applications wit…
RuBia: A Russian Language Bias Detection Dataset
Veronika Grigoreva, Anastasiia Ivanova, Ilseyar Alimova +1
Warning: this work contains upsetting or disturbing content. Large language models (LLMs) tend to learn the social and cultural biases present in the raw pre-training data. To test…
Sinkhorn Transformations for Single-Query Postprocessing in Text-Video Retrieval
Konstantin Yakovlev, Gregory Polyakov, Ilseyar Alimova +4
A recent trend in multimodal retrieval is related to postprocessing test set results via the dual-softmax loss (DSL). While this approach can bring significant improvements, it usu…
Selection of pseudo-annotated data for adverse drug reaction classification across drug groups
Ilseyar Alimova, Elena Tutubalina
Automatic monitoring of adverse drug events (ADEs) or reactions (ADRs) is currently receiving significant attention from the biomedical community. In recent years, user-generated d…
The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews
Elena Tutubalina, Ilseyar Alimova, Zulfat Miftahutdinov +3
The Russian Drug Reaction Corpus (RuDReC) is a new partially annotated corpus of consumer reviews in Russian about pharmaceutical products for the detection of health-related named…