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20242026
most citedMultimodal Evaluation of Russian-language Architectures

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

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cs.CL2026

Learning Selective LLM Autonomy from Copilot Feedback in Enterprise Customer Support Workflows

Nikita Borovkov, Elisei Rykov, Olga Tsymboi +4

We present a deployed system that automates end-to-end customer support workflows inside an enterprise Business Process Management (BPM) platform. The approach is scalable in produ…

cs.CL20261 cited

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…

cs.CL2025

When Models Lie, We Learn: Multilingual Span-Level Hallucination Detection with PsiloQA

Elisei Rykov, Kseniia Petrushina, Maksim Savkin +6

Hallucination detection remains a fundamental challenge for the safe and reliable deployment of large language models (LLMs), especially in applications requiring factual accuracy.…

cs.CL2024

SmurfCat at PAN 2024 TextDetox: Alignment of Multilingual Transformers for Text Detoxification

Elisei Rykov, Konstantin Zaytsev, Ivan Anisimov +1

This paper presents a solution for the Multilingual Text Detoxification task in the PAN-2024 competition of the SmurfCat team. Using data augmentation through machine translation a…

cs.CL2024

S3: A Simple Strong Sample-effective Multimodal Dialog System

Elisei Rykov, Egor Malkershin, Alexander Panchenko

In this work, we present a conceptually simple yet powerful baseline for the multimodal dialog task, an S3 model, that achieves near state-of-the-art results on two compelling lead…

cs.CL2024

SmurfCat at SemEval-2024 Task 6: Leveraging Synthetic Data for Hallucination Detection

Elisei Rykov, Yana Shishkina, Kseniia Petrushina +3

In this paper, we present our novel systems developed for the SemEval-2024 hallucination detection task. Our investigation spans a range of strategies to compare model predictions…