3 citations · 3 across the 7 of their papers we have counts for
8 papers
How Many Trees in a Random Forest? A Revisited Approach with Plateau Search and Optuna Integration
Vadim Porvatov, Andrey Dukhovny, Andrey Lange
Hyperparameter optimization (HPO) for Random Forest faces a specific difficulty in tuning the number of trees: the predictive score typically improves monotonically with ensemble s…
Beyond Early-Token Bias: Model-Specific and Language-Specific Position Effects in Multilingual LLMs
Mikhail Menschikov, Alexander Kharitonov, Maiia Kotyga +5
Large Language Models (LLMs) exhibit position bias systematically underweighting information based on its location in the context but how this bias varies across languages and mode…
GCT-TTE: Graph Convolutional Transformer for Travel Time Estimation
Vladimir Mashurov, Vaagn Chopurian, Vadim Porvatov +2
This paper introduces a new transformer-based model for the problem of travel time estimation. The key feature of the proposed GCT-TTE architecture is the utilization of different…
Revising deep learning methods in parking lot occupancy detection
Anastasia Martynova, Mikhail Kuznetsov, Vadim Porvatov +4
Parking guidance systems have recently become a popular trend as a part of the smart cities' paradigm of development. The crucial part of such systems is the algorithm allowing dri…
5q032e@SMM4H'22: Transformer-based classification of premise in tweets related to COVID-19
Vadim Porvatov, Natalia Semenova
Automation of social network data assessment is one of the classic challenges of natural language processing. During the COVID-19 pandemic, mining people's stances from public mess…
Logistics, Graphs, and Transformers: Towards improving Travel Time Estimation
Natalia Semenova, Vadim Porvatov, Vladislav Tishin +2
The problem of travel time estimation is widely considered as the fundamental challenge of modern logistics. The complex nature of interconnections between spatial aspects of roads…