Martin Fajčík
Postdoctoral Researcher in Natural Language Processing at BUT - Faculty of Information Technology
VOL_15
8 April 2025 at 5 pm
online
Language as an Ally: Benchmarking LLMs for Small Languages and Using Natural Language Supervision for Improving ML Results
The 15th edition of Better AI Meetup will be held in Brno! The university in Brno has a deep focus on modern technologies – and a sizeable Slovak diaspora. We will be talking about different aspects of language models and their role.
In the first presentation, Martin Fajčík from FIT at VUT, Brno will introduce the very first benchmark for LLMs in the Czech language: BenCzechMark. Small languages are not well-represented in large language models, which creates specific challenges when using them in real-life applications – and proper benchmarking can help choose the right model for the job.
In the second part of the evening, Jakub Špaňhel from Innovatrics will show us how they used natural language supervision to increase accuracy and robustness in the process usually done only via image processing – liveness checks and deepfake detection. In this case, machine learning benefits from natural language supervision even in image-related tasks.
_Supported by
_Speakers
Martin Fajčík is a postdoctoral researcher at Brno University of Technology, dedicated to improving and understanding language models in areas such as machine comprehension, information retrieval, and fact-checking. In past, Martin focused on retrieval-augmented QA systems, such as the R2-D2 system, which attained 3rd place in the prestigious EfficientQA@NeurIPS challenge, or led a team that built the first Czech Large Language Model CSMPT-7B and BenCzechMark: the first Czech-centric Multitask and Multimetric Benchmark.
Jakub Špaňhel
AI Solution Expert at Innovatrics
Jakub is an AI Solution Expert & Liveness Team Lead at Innovatrics R&D in Brno. His team combats identity fraud in IDV systems by developing AI-driven Liveness & Deepfake detection for secure Digital Onboarding. Their solutions verify whether a selfie is genuine or a digital or presentation attack.
During his PhD at Brno University of Technology, he specialized in AI and image processing for traffic surveillance and continues there as a postdoctoral researcher, focusing on biometrics.
_Agenda
Language: English
5:00 pm
_Introduction
5:05 pm
_Martin Fajčík, FIT Brno - On the Evaluation of Czech LLMs with BenCzechMark and Beyond
5:30 pm
_Jakub Špaňhel - Securing Digital Onboarding: The Role of Natural Language in Machine Learning for Identity Verification
5:55 pm
_Q&A
6:30 pm
_Closing
_Sign up
Past Meetups
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We will be discussing the uses of AI with the specialists from the largest Slovak banks and we will even welcome a guest from the banking regulator to shed light on their stance on using AI in financial services.
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Join us to see how AI will be helping you get healthier in the coming future!
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During the 8th Better AI Meetup, we will be addressing exactly these challenges: evaluating quality of language models, training those models without breaking the bank and the future expectations from language models in the business and elsewhere.
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In this edition of Better AI Meetup we will be talking about speech processing as well as designing ways to evaluate machine learning algorithms for accuracy and speed and choose a proper one for a particular use case.
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We will present two practical examples on how to use generative AI for improving datasets for machine learning.
Lukáš will show us how to use AI for annotation and labeling of large datasets, while Igor has developed novel ways to generate fingerprints for training fast, accurate models for fragmented fingerprints. In both cases, AI is helping improve the accuracy of models that then help automate administrative processes or even solve crimes.
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Ever wanted to start utilizing federated learning? Professor Peter Richtarik from King Abdullah University of Science and Technology will give us a detailed lecture on the role of local training in federated learning and will answer any questions you may have.
Federated Learning refers to machine learning over private data stored across a large number of heterogeneous devices, such as mobile phones or hospitals. In an October 2020 Forbes article, and alongside self-supervised learning and transformers, Federated Learning was described as one of three emerging areas that will shape the next generation of AI technologies. In this talk I will explain how we recently resolved one of the key open algorithmic and mathematical problems in this field.
AI Meets Humans: The Challenges of Introducing ML Models into Everyday Life
What happens when research, its practical applications and human factor intersect? How to train the machine learning models to expect the unpredictable events that are inevitable in real life? This time we’ll look at the challenges the AI and ML technologies face when put to practical use.
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Machine learning (ML) helped us to solve such complex tasks as face recognition, however when it is done on a large scale it relies on many high-effort data management tasks. We will describe our winding road from images in folders and labels stored in CSV files to structured versioned datasets with reproducible data processing pipelines. Moreover we mention how we deal with data versioning / validation / quality evaluation, reproducible ML trainings and experiment management.
First ever Slovak language neural model and why AI is becoming mainstream
The opening presentation is centered on the most recent success of AI research in Slovakia – the SlovakBERT model. Creating a neural language model for languages with limited available corpus can be challenging. We will explain what are the main obstacles when creating such model and what its practical applications are. The second presentation will focus on why AI is becoming mainstream and what it means for the future of the technology.
