Viktor Moskvoretskii

HSE, online

• Project on enhancing LLM with Taxonomic structures
• {"led to the LREC-COLING 2024 paper Are Large Language Models Good at Lexical Semantics? A Case of Taxonomy Learning, to the ACL 2024 paper TaxoLLaMA\\"=>"WordNet-based Model for Solving Multiple Lexical Sematic Tasks and to Low-Resource Machine Translation through the Lens of Personalized Federated Learning"}

Ahmad Shallouf

Universität Hamburg

• {"master thesis ”CompGLUE\\"=>"Datasets and Evaluation System for Comparative Question Answering Tasks”"}
• {"led to the LREC-COLING 2024 paper CAM 2.0"=>"End-to-End Open Domain Comparative Question Answering System"}

Angel Ontiveros

Universität Hamburg

• master thesis ”Development and Evaluation of an IT Tool for ESG Compliance Consulting for Companies Using LLMs”

Jan Strich

Universität Hamburg

• master thesis ”Improving Large Language Models in Repository Level Programming through Self-Alignment and Retrieval-Augmented Generation”
• co-supervisor Florian Schneider

Maria Manina, Daria Ignatenko, Nikolay Dolgov

HSE University

• master project supervision ”Benchmark system for Comparative Question Answering”

Alina Rechina

HSE University

• consultant for the BSc student thesis with Viktor Moskvoretskii
• title ”Multilingual Large Language Models for predicting IS-A relationships”
• {"led to ACL 2024 paper TaxoLLaMA"=>"WordNet-based Model for Solving Multiple Lexical Sematic Tasks”"}

Ekaterina Neminova

HSE University

• consultant for the BSc student thesis with Viktor Moskvoretskii
• title ”Investigation of Large Language Models for Taxonomy-related Tasks”
• {"led to ACL 2024 paper TaxoLLaMA"=>"WordNet-based Model for Solving Multiple Lexical Sematic Tasks”"}

Ahmad Shallouf, Hannah Herasimchyk, Rudy Garrido Veliz, Natia Mestvirishvii

Universität Hamburg

• {"led to the LREC-COLING 2024 paper CAM 2.0"=>"End-to-End Open Domain Comparative Question Answering System"}

Maria Maslova, Stefan Rebrikov

HSE University

• master project supervision ”Russian Comparative Argumentative Machine”
• {"led to the AIST 2023 paper ”RuCAM"=>"Russian Comparative Argumentative Machine”"}

Polina Chernomorchenko

HSE University

• BSc student thesis supervision ”Automatic Taxonomy Enrichment Using Generative Models”
• led to the led to 2 papers published at AACL-2023 and AIST-2023 conferences ”Predicting Terms in IS-A Relations with Pre-trained Transformers” and ”Leveraging Taxonomic Information from Large Language Models for Hyponymy Prediction”

Alsu Vakhitova

Skoltech

• MSc student thesis supervision ”Candidate-free taxonomy enrichment with pre-trained neural language models”
• {"led to the led to 2 papers published at AACL-2022 and TextGraph-16 Workshop ”TaxFree"=>"a Visualization Tool for Candidate-free Taxonomy Enrichment” and ”Cross-modal contextualized hidden state projection method for expanding of taxonomic graphs”"}

Anna Safaryan, Petr Filchenkov, Weijia Yan

HSE University

• MSc student project co-supervision with Andrey Kutuzov
• led to a paper published at AIST-2020 ”Semantic Recommendation System for Bilingual Corpus of Academic Papers”

Lecture on Encoder and Decoder Transformers (en)

AI & DT school on Transformers

• duration 1 hour,
• audience Generative AI school participants

Course on Transformers

MSc students & Data Scientists in the Industry

• github repository, paper with the course description, accepted to TeachNLP ACL workshop

Web interfaces for Language Technology Systems

Universität Hamburg

• audience MSc students in Computer Science

Neural Natural Language Processing (en)

HSE University, online

• duration Terms 1 and 2
• audience 4th year BSc students in Fundamental and Applied Linguistics
• links Github

Machine Learning 2 (en)

HSE University, online

• duration Terms 2 and 3
• audience 4th year BSc students in Data Science and Business Analytics

Neural Natural Language Processing (en)

HSE University, online

• duration Term 4
• audience MSc students in Computer Scince

Statistical Natural Language Processing (en)

HSE University, online

• Course link
• duration Term 2
• audience MSc students in Computer Scince

Applied Research in Culture (ru)

HSE University, online

• Course link, Github
• duration Term 1
• audience MSc students in Applied Cultural Studies

Programming and Linguistic Data (ru)

HSE University

• Course link, Github
• duration Terms 1-4
• audience 1st year BSc students in Applied Linguistics

Digital Literacy (ru)

HSE University

• Course link, Github
• duration Terms 1-4
• 1st year BSc students in Applied Cultural Studies