16 citations · 16 across the 4 of their papers we have counts for
4 papers
ML2B: Benchmarking LLMs on Cross-Lingual ML Pipeline Generation
Ekaterina Trofimova, Zosia Shamina, Maria Selifanova +7
We introduce ML2B, the first benchmark for evaluating cross-lingual task comprehension in end-to-end ML pipeline generation by large language models. Despite growing global AI adop…
Predicting ionic conductivity in solids from the machine-learned potential energy landscape
Artem Maevskiy, Alexandra Carvalho, Emil Sataev +5
Discovering new superionic materials is essential for advancing solid-state batteries, which offer improved energy density and safety compared to the traditional lithium-ion batter…
CodeRefine: A Pipeline for Enhancing LLM-Generated Code Implementations of Research Papers
Ekaterina Trofimova, Emil Sataev, Abhijit Singh Jowhari
This paper presents CodeRefine, a novel framework for automatically transforming research paper methodologies into functional code using Large Language Models (LLMs). Our multi-ste…
Linguacodus: A Synergistic Framework for Transformative Code Generation in Machine Learning Pipelines
Ekaterina Trofimova, Emil Sataev, Andrey E. Ustyuzhanin
In the ever-evolving landscape of machine learning, seamless translation of natural language descriptions into executable code remains a formidable challenge. This paper introduces…