no code implementations • WMT (EMNLP) 2020 • Karen Hambardzumyan, Hovhannes Tamoyan, Hrant Khachatrian
This report describes YerevaNN’s neural machine translation systems and data processing pipelines developed for WMT20 biomedical translation task.
no code implementations • 12 Dec 2024 • Edvard Ghukasyan, Hrant Khachatrian, Rafayel Mkrtchyan, Theofanis P. Raptis
Vision Transformers (ViTs) have demonstrated remarkable success in achieving state-of-the-art performance across various image-based tasks and beyond.
1 code implementation • 4 Oct 2024 • Hrayr Harutyunyan, Rafayel Darbinyan, Samvel Karapetyan, Hrant Khachatrian
We show that it is possible to obtain an in-context learner that generalizes to unseen tasks by training on a diverse dataset of synthetic in-context learning instances.
1 code implementation • 26 Jul 2024 • Philipp Guevorguian, Menua Bedrosian, Tigran Fahradyan, Gayane Chilingaryan, Hrant Khachatrian, Armen Aghajanyan
Recent advancements in large language models have opened new possibilities for generative molecular drug design.
no code implementations • 27 Feb 2024 • 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 coverage, susceptibility to environmental conditions, and high computational and energy demands.
no code implementations • 31 Dec 2023 • Ani Vanyan, Alvard Barseghyan, Hakob Tamazyan, Vahan Huroyan, Hrant Khachatrian, Martin Danelljan
In this paper, we present a comparative analysis of various self-supervised Vision Transformers (ViTs), focusing on their local representative power.
no code implementations • 22 Jun 2023 • Rafayel Darbinyan, Hrayr Harutyunyan, Aram H. Markosyan, Hrant Khachatrian
Neural networks employ spurious correlations in their predictions, resulting in decreased performance when these correlations do not hold.
no code implementations • 22 Apr 2023 • Rafayel Darbinyan, Hrant Khachatrian, Rafayel Mkrtchyan, Theofanis P. Raptis
The challenging problem of non-line-of-sight (NLOS) localization is critical for many wireless networking applications.
1 code implementation • 29 Nov 2022 • Gayane Chilingaryan, Hovhannes Tamoyan, Ani Tevosyan, Nelly Babayan, Lusine Khondkaryan, Karen Hambardzumyan, Zaven Navoyan, Hrant Khachatrian, Armen Aghajanyan
We then quantitatively show that when applied to the molecular domain, the BART objective learns representations that implicitly encode our downstream tasks of interest.
1 code implementation • CVPR 2022 • Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
On Camelyon-17, domain-invariance degrades the quality of representations on unseen domains.
1 code implementation • ACL 2021 • Karen Hambardzumyan, Hrant Khachatrian, Jonathan May
Transfer learning from pretrained language models recently became the dominant approach for solving many NLP tasks.
no code implementations • 10 Jul 2020 • Tigran Galstyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
Investigation of machine learning algorithms robust to changes between the training and test distributions is an active area of research.
2 code implementations • CVPR 2020 • Mang Tik Chiu, Xingqian Xu, Yunchao Wei, Zilong Huang, Alexander Schwing, Robert Brunner, Hrant Khachatrian, Hovnatan Karapetyan, Ivan Dozier, Greg Rose, David Wilson, Adrian Tudor, Naira Hovakimyan, Thomas S. Huang, Honghui Shi
To encourage research in computer vision for agriculture, we present Agriculture-Vision: a large-scale aerial farmland image dataset for semantic segmentation of agricultural patterns.
1 code implementation • WS 2019 • Hrant Khachatrian, Lilit Nersisyan, Karen Hambardzumyan, Tigran Galstyan, Anna Hakobyan, Arsen Arakelyan, Andrey Rzhetsky, Aram Galstyan
Automatic extraction of relations and interactions between biological entities from scientific literature remains an extremely challenging problem in biomedical information extraction and natural language processing in general.
1 code implementation • Nature Scientific Data 2019 • Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Greg Ver Steeg, Aram Galstyan
Health care is one of the most exciting frontiers in data mining and machine learning.
2 code implementations • 30 May 2019 • Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan
Estimating the covariance structure of multivariate time series is a fundamental problem with a wide-range of real-world applications -- from financial modeling to fMRI analysis.
1 code implementation • CONLL 2018 • Gor Arakelyan, Karen Hambardzumyan, Hrant Khachatrian
This paper describes our submission to CoNLL 2018 UD Shared Task.
1 code implementation • 9 Feb 2018 • Martin Mirakyan, Karen Hambardzumyan, Hrant Khachatrian
We have tried to reproduce the results of the paper "Natural Language Inference over Interaction Space" submitted to ICLR 2018 conference as part of the ICLR 2018 Reproducibility Challenge.
11 code implementations • 22 Mar 2017 • Hrayr Harutyunyan, Hrant Khachatrian, David C. Kale, Greg Ver Steeg, Aram Galstyan
Health care is one of the most exciting frontiers in data mining and machine learning.