YerevaNN

Research

• [2024] Small Molecule Optimization with Large Language Models. [preprint] [code] (with Armen Aghajanyan)
• [2022] BARTSmiles: large-scale generative masked language models for molecular representations . [preprint] [code] (with IMB NAS RA, Toxometris.ai and Meta AI)
• [2022] Improved molecular representations for property prediction based on VAEs. Published in Journal of Cheminformatics. (with Institute of Molecular Biology NAS RA).
• [2020] Parasite: a method to align sentences in parallel corpora [code]. Helped to win WMT'20 Biomedical Translation Shared Task for en-ru pairs [paper].
• [2019] BioRelEx: biological relation extraction dataset [data] [baselines] Published in BioNLP'19 workshop (with USC ISI and Bioinformatics group at IMB NAS RA, as part of the Big Mechanism program)
• [2018] Clinical time series prediction benchmarks [code] [pretrained models]. Published in Nature Scientific Data (with USC ISI)

• [2024] In-context learning in presence of spurious correlations. [paper] (with Hrayr Harutyunyan, Google Research). Published at ICML 2024 Workshop on In-Context Learning.
• [2023] Identifying and disentangling spurious features in pretrained image representations. [preprint] (with Meta AI and USC ISI). Accepted at ICML 2023 Workshop on Spurious Correlations, Invariance and Stability.
• [2021] Characterization of the failure modes of domain generalization algorithms. Published in CVPR'22 (with USC ISI).
• [2020] Robust classification under class-dependent domain shift [preprint] (with USC ISI). Presented at ICML 2020 UDL Workshop

• [2024] Analyzing Local Representations of Self-supervised Vision Transformers. [preprint] (with Martin Danielljan)
• [2023] Scaling laws for mixed-modal language models. [preprint] (with Meta AI)
• [2023] Wireless non-line-of-sight localization of a device using a single antenna in an urban environment Accepted at IEEE Big Data Service 2023. [preprint] (with Yerevan State University and CNR Institute of Informatics and Telematics)
• [2022] Matching map recovery with an unknown number of outliers. Published in AISTATS'23 [preprint] (with ENSAE-CREST)
• [2022] GradSkip: an extension of a local gradient method for distributed optimization that supports variable number of local gradient steps in each communication round. [preprint] (with KAUST)
• [2021] WARP: a parameter-efficient method for transfer learning in NLP. Published in ACL'21 (with USC ISI)
• [2021] Theoretical analysis of the detection of the feature matching map in presence of outliers. Published in Electronic Journal of Statistics (with ENSAE-CREST)
• [2021] A survey of deep neural networks for semi-supervised image classification. Published in JUCS.
• [2020] A novel robust estimator of the mean of a multivariate Gaussian distribution. Published in Annals of Statistics (with ENSAE-CREST)
• [2019] T-Corex: a novel method for temporal covariance estimation using information theoretic apparatus [preprint] [code] (with USC ISI)

• Eastern Armenian treebank as part of the Universal Dependencies project [data (52K tokens)] [website] [code]
• An end-to-end syntax parser for Armenian [code] [demo]
• Collaboration with Marat Yavrumyan and Anna Danielyan from Yerevan State University. Partially funded by ANSEF, ISTC and Gulbenkian Foundation.