115 citations · 195 across the 32 of their papers we have counts for
5 papers · 2 filters
Drawing Pandas: A Benchmark for LLMs in Generating Plotting Code
Timur Galimzyanov, Sergey Titov, Yaroslav Golubev +1
This paper introduces the human-curated PandasPlotBench dataset, designed to evaluate language models' effectiveness as assistants in visual data exploration. Our benchmark focuses…
EM-Assist: Safe Automated ExtractMethod Refactoring with LLMs
Dorin Pomian, Abhiram Bellur, Malinda Dilhara +5
Excessively long methods, loaded with multiple responsibilities, are challenging to understand, debug, reuse, and maintain. The solution lies in the widely recognized Extract Metho…
Kotlin ML Pack: Technical Report
Sergey Titov, Mikhail Evtikhiev, Anton Shapkin +7
In this technical report, we present three novel datasets of Kotlin code: KStack, KStack-clean, and KExercises. We also describe the results of fine-tuning CodeLlama and DeepSeek m…
Tool-Augmented LLMs as a Universal Interface for IDEs
Yaroslav Zharov, Yury Khudyakov, Evgeniia Fedotova +2
Modern-day Integrated Development Environments (IDEs) have come a long way from the early text editing utilities to the complex programs encompassing thousands of functions to help…
Together We Go Further: LLMs and IDE Static Analysis for Extract Method Refactoring
Dorin Pomian, Abhiram Bellur, Malinda Dilhara +4
Long methods that encapsulate multiple responsibilities within a single method are challenging to maintain. Choosing which statements to extract into new methods has been the targe…