Program

Keynote Speakers

Illia Strelnykov, Data Scientist at YouScan, Ukraine

Topic: Leveraging User Feedback to Improve Your Models

While academic research provides a strong foundation for model development, the ultimate goal is to deploy these models in real-world applications, where they interact with actual users. This talk addresses the critical challenge of effectively leveraging user feedback to enhance model performance in practical scenarios. We’ll explore ways to incorporate the highly valuable — yet inherently noisy — user-provided data into model training and fine-tuning pipelines. First, we’ll cover methods for collecting user feedback and the challenges involved in processing it, including issues like bias and conflicting information. Then we will examine various solutions for tackling these challenges and how to use refined feedback for model improvement.

Sebastian Ruder, Research Scientist at Meta, Germany

Topic: Multilinguality in Llama 4 and Beyond

Abstract: Multilingual LLMs have become so powerful that they can be used in real-world conversations in a variety of applications. While this presents many opportunities, it also poses challenges associated with the complexity of natural language. In this talk, I will seek to connect academic research to real-world challenges of multilingual conversational AI. I will first provide an overview of multilinguality in Llama 4, highlighting the importance of evaluation. I will then discuss what it takes to bridge the gap between academic and real-world evaluations. Finally, I will discuss how we can develop models that are useful to speakers in their local context, across the globe and for the Ukrainian language.

Panelists

Kateryna Burovova, ML Engineer at LetsData

Kateryna specializes in AI-powered solutions for detecting and combating harmful information operations, leveraging NLP and computational social science to create threat detection pipelines that analyze content semantics, user behavior patterns, network dynamics, and other contextual signals.

Nataliia Romanyshyn, AI Specialist at Texty.org.ua

Nataliia focuses on the detection and analysis of Russian disinformation. Her expertise includes natural language processing, specifically topic modeling, named entity recognition, large language models, and multilingual NLP. She plays a key role in developing analytical frameworks that transform complex textual data into actionable insights aimed at uncovering disinformation mechanisms.

Yaroslav Peliushenko, Head of Analytics at Osavul

Yaroslav is the Head of Analysis at Osavul, a technology company developing AI-powered solutions for deep intelligence and countering information threats. At UNLP, he will share insights into how their team analyses and structures information, the frameworks they use, and the thinking behind their approach.

Yuliia Dukach, PhD, Data Journalist and Head of Disinformation Investigations at OpenMinds

Yuliia is an expert in disinformation research with over five years of experience in investigative data journalism. Yuliia applies advanced skills in Python and machine learning to analyze computational propaganda and online misinformation.

Vasyl Starko, Ukrainian Catholic University, Ukraine

Andriy Rysin, Independent researcher, USA

Topic: BRUK Team’s Resources for Ukrainian Corpus Creation

The talk will focus on the key resources and tools developed by the BRUK team for the automatic processing of Ukrainian texts, especially for building Ukrainian corpora. The resources include:

* BRUK (Ukrainian Brown Corpus, a projected one-million-word POS gold standard)

* VESUM (A Large Electronic Dictionary of Ukrainian, over 420,000 lemmas and counting, for POS tagging)

* USL (Ukrainian Semantic Lexicon for semantic tagging).

The tools come in the form of the NLP_UK suite for Ukrainian text tokenization, lemmatization, POS tagging, and cleaning. The application of NLP_UK to build multiple iterations of the GRAC corpus will be discussed.