Publications

2025

Hovhannes Tamoyan, Subhabrata Dutta, and Iryna Gurevych. "Factual Self-Awareness in Language Models: Representation, Robustness, and Scaling." arXiv preprint arXiv:2505.21399 (2025).
Hovhannes Tamoyan, Hendrik Schuff, and Iryna Gurevych. "Llm roleplay: Simulating human-chatbot interaction." Proceedings of the Third Workshop on Social Influence in Conversations (SICon 2025). 2025.

2023

Yu, Lili, et al. "Scaling autoregressive multi-modal models: Pretraining and instruction tuning (2023)." URL https://arxiv.org/abs/2309.02591.

2022

Hovhannes Tamoyan, Gayane Chilingaryan, Ani Tevosyan, et al. "BARTSmiles: Generative Masked Language Models for Molecular Representations. arXiv 2022." arXiv preprint arXiv:2211.16349.

2020

Karen Hambardzumyan, Hovhannes Tamoyan, and Hrant Khachatrian. "YerevaNN's Systems for WMT20 Biomedical Translation Task: The Effect of Fixing Misaligned Sentence Pairs." Proceedings of the Fifth Conference on Machine Translation. 2020.

Projects

Tools

Urartu

ML pipeline framework with smart caching and remote execution. Chain actions into workflows, run anywhere — local machines to HPC clusters. YAML-configured with built-in experiment tracking and SLURM integration.

OrganizeNoc

Browser extension suite for researchers to manage academic papers library. Features metadata extraction, highlight processing, citation BibTeX export, and AI-powered querying.

Aim

Open-source experiment tracking tool designed with flexibility for machine learning workflows. Facilitates detailed monitoring and comparison of experiments.

tmynNLP

Natural language processing pipeline equipped with mainstream abstractions. Supports a diverse array of NLP tasks.

Teaching

Experiment Tracking - Workshop

Essentials of experiment tracking in ML research, with an in-depth exploration of Aim and a practical demonstration integrating it into an NMT fine-tuning pipeline.

LxMLS Guide - Summer School

Lisbon Machine Learning Summer School lab guide with setup instructions, toolkit walkthroughs, and hands-on exercises.

PyTorch Optimization - Workshop

Strategies for efficient dataloader usage, parallel computation, operator fusing, and more to enhance PyTorch code performance.

Resume (download)

Education

Ph.D, Computer Science, Technical University of Darmstadt

Research Areas: Natural Language Processing, Code Generation, Reasoning and Interpretability
Supervisor: Prof. Dr. Mira Mezini
2023 – present

M.Sc., Computer Science, American University of Armenia

Supervisor: Karen Hambardzumyan
2019 – 2021

B.Sc., Nuclear Physics, Yerevan State University

Supervisor: Prof. Dr. Vasili Tsakanov
2015 – 2019

Work Experience

Applied Research Intern, NVIDIA, San Francisco Bay Area, CA

  • Research on improving Reasoning Language Models capabilities on STEM domain.
03/2026 – present

Applied Research Intern, NVIDIA, Yerevan, Armenia

  • Improved code-reasoning performance of open-source LLMs on SWE-Bench through targeted evaluation, error analysis, and iterative modeling iterations.
  • Built a localization system Artsiv achieving state-of-the-art results on SWE-Bench (1 publication).
05/2025 – 09/2025

Doctoral Researcher, Technical University of Darmstadt, Darmstadt, Germany

  • Conducted mechanistic interpretability research to predict pre-generation instabilities and hallucinations (factual self-unawareness) at inference time in LLMs (2 publications).
  • Created multi-agent system to generate human-chatbot interaction dialogues at scale (1 publication).
  • Developed Urartu, a lightweight slurm submission + reproducibility framework for faster iteration.
03/2023 – 02/2026

Machine Learning Researcher, YerevaNN, Yerevan, Armenia

  • Investigated interpretability of the Chameleon model (FAIR, Meta AI collaboration) (1 publication).
  • Researched transformer alternatives for text generation: diffusion models, mixture of expert models, and language model bootstrapping (FAIR, Meta AI collaboration).
  • Trained a molecular representation learning model (FAIR, Meta AI collaboration) (1 publication).
  • Experimented on cross-lingual zero-shot transfer using prompt-based learning and adapters.
  • Researched bilingual sentence alignment in low-resource setups (Master’s Thesis).
  • Built a machine translation system for the WMT20 Biomedical domain tasks (1 publication).
09/2020 – 02/2023

Machine Learning Engineer, AimStack, Yerevan, Armenia

  • Integrated the Aim experiment tracking tool with popular ML frameworks and MLOps tools.
  • Authored technical blog posts to increase community awareness and adoption (3 blog posts).
08/2022 – 03/2023

Machine Learning Engineer, ZERØ, Yerevan, Armenia

  • Researched and developed a legal document classification system.
  • Built tmynNLP, a framework used to develop a multiclass document classification pipeline.
11/2021 – 03/2022

Software Engineer, Birthright Armenia, Yerevan, Armenia

  • Led and built a large-scale CMS system with email management system.
09/2019 – 07/2022

Physics Researcher, CANDLE SRI, Yerevan, Armenia

  • Measured electron-beam emittance on the AREAL linac (1 publication).
  • Built a tooling suite for accelerator control and beam diagnostics.
10/2018 – 11/2019

Web Developer, Floopen, Yerevan, Armenia

  • Developed and maintained a general-purpose content management system.
12/2017 – 11/2018

Teaching Experience

Teaching Associate, Technical University of Darmstadt, Darmstadt, Germany

  • Taught the Introduction to LLMs course as a Teaching Associate.
  • Conducted workshops on PyTorch optimization and experiment tracking and reproducibility.
  • Supervised 4 M.Sc. theses in mechanistic interpretability.
07/2024 – 02/2026

Core Monitor, Instituto Superior Técnico – LxMLS 2023, Lisbon, Portugal

  • Authored a step-by-step guide explaining the transformer architecture.
  • Facilitated hands-on lab sessions for researchers, graduate students, and industry professionals.
07/2023

Teaching Associate, American University of Armenia, Yerevan, Armenia

  • Deep Learning: Taught natural language processing lectures and led problem-solving sessions.
  • Data Structures and Algorithms: Led problem-solving sessions and created homework assignments.
09/2021 – 12/2022

Skills

Computer Science: Algorithms Design, Data Structures

Languages: C, Python, CUDA, JavaScript

Machine Learning: PyTorch, xFormers, FairSeq/MetaSeq, AllenNLP, PyTorch Lightning

Database Systems: SQL, NoSQL, GraphQL