2 citations · 2 across the 7 of their papers we have counts for
6 papers · 1 filter
Belief Propagation in LLM World Models: Measuring Strategic Information Bias with Prediction Markets
Mykola Khandoga, Yevhen Kostiuk, Anton Polishko +4
Every information ecosystem produces beliefs that shape strategic decisions. Both human analysts and AI systems inherit the blind spots of their information sources. We show that L…
The Veln(ia)s is in the Details: Evaluating LLM Judgment on Latvian and Lithuanian Short Answer Matching
Yevhen Kostiuk, Oxana Vitman, Łukasz Gagała +1
In this work, we address the challenge of evaluating large language models (LLMs) on the short answer matching task for Latvian and Lithuanian languages. We introduce novel dataset…
Towards Multilingual LLM Evaluation for Baltic and Nordic languages: A study on Lithuanian History
Yevhen Kostiuk, Oxana Vitman, Łukasz Gagała +1
In this work, we evaluated Lithuanian and general history knowledge of multilingual Large Language Models (LLMs) on a multiple-choice question-answering task. The models were teste…
Benchmarking Multimodal Models for Ukrainian Language Understanding Across Academic and Cultural Domains
Yurii Paniv, Artur Kiulian, Dmytro Chaplynskyi +4
While the evaluation of multimodal English-centric models is an active area of research with numerous benchmarks, there is a profound lack of benchmarks or evaluation suites for lo…
From English-Centric to Effective Bilingual: LLMs with Custom Tokenizers for Underrepresented Languages
Artur Kiulian, Anton Polishko, Mykola Khandoga +10
In this paper, we propose a model-agnostic cost-effective approach to developing bilingual base large language models (LLMs) to support English and any target language. The method…
From Bytes to Borsch: Fine-Tuning Gemma and Mistral for the Ukrainian Language Representation
Artur Kiulian, Anton Polishko, Mykola Khandoga +4
In the rapidly advancing field of AI and NLP, generative large language models (LLMs) stand at the forefront of innovation, showcasing unparalleled abilities in text understanding…