3 citations · 7 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
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…
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…
Comparative Analysis of Encoder-Based NER and Large Language Models for Skill Extraction from Russian Job Vacancies
Nikita Matkin, Aleksei Smirnov, Mikhail Usanin +4
The labor market is undergoing rapid changes, with increasing demands on job seekers and a surge in job openings. Identifying essential skills and competencies from job description…