collaborators

5 papers

cs.CL2026

A Komi-Yazva--Russian Parallel Corpus and Evaluation Protocol for Zero- and Few-Shot LLM Translation

Petr Parshakov

We present the first Komi-Yazva--Russian parallel corpus together with an explicit evaluation protocol for studying LLM translation in an endangered, extremely low-resource setting…

econ.GN2026

Not Yet: Humans Outperform LLMs in a Colonel Blotto Tournament

Dmitry Dagaev, Egor Ivanov, Petr Parshakov +2

The emergence of large language models (LLMs) has spurred economists to study how humans and LLMs behave in strategic settings. We organized a series of round-robin tournaments in…

cs.CL2026

AI-based approach to burnout identification from textual data

Marina Zavertiaeva, Petr Parshakov, Mikhail Usanin +3

This study introduces an AI-based methodology that utilizes natural language processing (NLP) to detect burnout from textual data. The approach relies on a RuBERT model originally…

econ.GN2025

Strategizing with AI: Insights from a Beauty Contest Experiment

Iuliia Alekseenko, Dmitry Dagaev, Sofia Paklina +1

A -beauty contest is a wide class of games of guessing the most popular strategy among other players. In particular, guessing a fraction of a mean of numbers chosen by all playe…

cs.HC2025

Users Favor LLM-Generated Content -- Until They Know It's AI

Petr Parshakov, Iuliia Naidenova, Sofia Paklina +2

In this paper, we investigate how individuals evaluate human and large langue models generated responses to popular questions when the source of the content is either concealed or…