activity
20232026
most citedCerberusDet: Unified Multi-Dataset Object Detection

1 citations · 2 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CV2026

VIBE: Visual Instruction Based Editor

Grigorii Alekseenko, Aleksandr Gordeev, Irina Tolstykh +7

Instruction-based image editing is among the fastest developing areas in generative AI. Over the past year, the field has reached a new level, with dozens of open-source models rel…

cs.CL2025

LLMTrace: A Corpus for Classification and Fine-Grained Localization of AI-Written Text

Irina Tolstykh, Aleksandra Tsybina, Sergey Yakubson +1

The widespread use of human-like text from Large Language Models (LLMs) necessitates the development of robust detection systems. However, progress is limited by a critical lack of…

cs.CV2025

NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining

Maksim Kuprashevich, Grigorii Alekseenko, Irina Tolstykh +4

Recent advances in generative modeling enable image editing assistants that follow natural language instructions without additional user input. Their supervised training requires m…

cs.CL2024

GigaCheck: Detecting LLM-generated Content via Object-Centric Span Localization

Irina Tolstykh, Aleksandra Tsybina, Sergey Yakubson +3

With the increasing quality and spread of LLM assistants, the amount of generated content is growing rapidly. In many cases and tasks, such texts are already indistinguishable from…

cs.CV2024

Saliency-Guided DETR for Moment Retrieval and Highlight Detection

Aleksandr Gordeev, Vladimir Dokholyan, Irina Tolstykh +1

Existing approaches for video moment retrieval and highlight detection are not able to align text and video features efficiently, resulting in unsatisfying performance and limited…

cs.CV2024★ 1 cited

CerberusDet: Unified Multi-Dataset Object Detection

Irina Tolstykh, Mikhail Chernyshov, Maksim Kuprashevich

Conventional object detection models are usually limited by the data on which they were trained and by the category logic they define. With the recent rise of Language-Visual Model…

cs.CV2024

Beyond Specialization: Assessing the Capabilities of MLLMs in Age and Gender Estimation

Maksim Kuprashevich, Grigorii Alekseenko, Irina Tolstykh

Multimodal Large Language Models (MLLMs) have recently gained immense popularity. Powerful commercial models like ChatGPT-4V and Gemini, as well as open-source ones such as LLaVA,…

cs.CV2023★ 1 cited

MiVOLO: Multi-input Transformer for Age and Gender Estimation

Maksim Kuprashevich, Irina Tolstykh

Age and gender recognition in the wild is a highly challenging task: apart from the variability of conditions, pose complexities, and varying image quality, there are cases where t…