3 citations · 3 across the 7 of their papers we have counts for
9 papers
Automated identification of quasi-BIC modes in disordered resonator chains using spatial field envelopes and resonance descriptors
Vadim A. Porvatov, Kliment V. Semushev, Ravshanjon Kh. Nazarov +4
Structural disorder turns bound states in the continuum (BICs) into quasi-BIC resonances and mixes them with spectrally close eigenmodes, so the target mode must be identified anew…
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…
Citation network applications in a scientific co-authorship recommender system
Vladislav Tishin, Artyom Sosedka, Peter Ibragimov +1
The problem of co-authors selection in the area of scientific collaborations might be a daunting one. In this paper, we propose a new pipeline that effectively utilizes citation da…
Hybrid Graph Embedding Techniques in Estimated Time of Arrival Task
Vadim Porvatov, Natalia Semenova, Andrey Chertok
Recently, deep learning has achieved promising results in the calculation of Estimated Time of Arrival (ETA), which is considered as predicting the travel time from the start point…