16 citations · 16 across the 4 of their papers we have counts for
5 papers
QuantCode Model: Specializing Language Models for Executable Algorithmic Trading Code
Alexey Chernysh, Orkhan Ekhtibarov, Dmitry Zmitrovich
Large language models are strong general-purpose code generators, but executable algorithmic trading remains a demanding specialization target: a model must translate a natural-lan…
Data-Centric Post-Training for Financial Reasoning: Mining, Distillation, and Verifiable Learning
Zhirayr Hayrapetyan, Andrei Kalmykov, Denis Kokosinskii +2
Financial text, textbooks, and question-answer pairs are abundant, but only a small fraction is directly usable for reasoning-focused post-training. Existing QA pairs often lack ex…
FINESSE-Bench: A Hierarchical Benchmark Suite for Financial Domain Knowledge and Technical Analysis in Large Language Models
Dmitry Stanishevskii, Nini Kamkia, Alexey Khoroshilov +4
Large language models (LLMs) are increasingly being applied to financial analysis, reporting, investment decision support, risk management, compliance, and professional training. H…
QuantCode-Bench: A Benchmark for Evaluating the Ability of Large Language Models to Generate Executable Algorithmic Trading Strategies
Alexey Khoroshilov, Alexey Chernysh, Orkhan Ekhtibarov +2
Large language models have demonstrated strong performance on general-purpose programming tasks, yet their ability to generate executable algorithmic trading strategies remains und…
A Family of Pretrained Transformer Language Models for Russian
Dmitry Zmitrovich, Alexander Abramov, Andrey Kalmykov +10
Transformer language models (LMs) are fundamental to NLP research methodologies and applications in various languages. However, developing such models specifically for the Russian…