15 citations · 34 across the 16 of their papers we have counts for
6 papers · 1 filter
Vision Transformers for Efficient Indoor Pathloss Radio Map Prediction
Rafayel Mkrtchyan, Edvard Ghukasyan, Khoren Petrosyan +2
Indoor pathloss prediction is a fundamental task in wireless network planning, yet it remains challenging due to environmental complexity and data scarcity. In this work, we propos…
In-context Learning in Presence of Spurious Correlations
Hrayr Harutyunyan, Rafayel Darbinyan, Samvel Karapetyan +1
Large language models exhibit a remarkable capacity for in-context learning, where they learn to solve tasks given a few examples. Recent work has shown that transformers can be tr…
Small Molecule Optimization with Large Language Models
Philipp Guevorguian, Menua Bedrosian, Tigran Fahradyan +3
Molecular optimization, the process of designing molecules with desirable properties, represents a critical challenge in drug discovery. The recent advancements in large language m…
Empirical Application Insights on Industrial Data and Service Aspects of Digital Twin Networks
Marco Becattini, Davide Borsatti, Armir Bujari +5
Digital twin networks (DTNs) serve as an emerging facilitator in the industrial networking sector, enabling the management of new classes of services, which require tailored suppor…
Outdoor Environment Reconstruction with Deep Learning on Radio Propagation Paths
Hrant Khachatrian, Rafayel Mkrtchyan, Theofanis P. Raptis
Conventional methods for outdoor environment reconstruction rely predominantly on vision-based techniques like photogrammetry and LiDAR, facing limitations such as constrained cove…
Analyzing Local Representations of Self-supervised Vision Transformers
Ani Vanyan, Alvard Barseghyan, Hakob Tamazyan +3
In this paper, we present a comparative analysis of various self-supervised Vision Transformers (ViTs), focusing on their local representative power. Inspired by large language mod…