3 papers
cs.SE2026
In-IDE Toolkit for Developers of AI-Based Features
Yaroslav Sokolov, Yury Khudyakov, Lenar Sharipov +3
AI-enabled features built on LLMs and agentic workflows are difficult to test, debug, and reproduce, especially for product-focused software engineers without a machine learning ba…
cs.HC2026
VegaChat: A Robust Framework for LLM-Based Chart Generation and Assessment
Marko Hostnik, Rauf Kurbanov, Yaroslav Sokolov +1
Natural-language-to-visualization (NL2VIS) systems based on large language models (LLMs) have substantially improved the accessibility of data visualization. However, their further…
cs.SE2025
Full Line Code Completion: Bringing AI to Desktop
Anton Semenkin, Vitaliy Bibaev, Yaroslav Sokolov +14
In recent years, several industrial solutions for the problem of multi-token code completion appeared, each making a great advance in the area but mostly focusing on cloud-based ru…