Making Bielik LLM Reason (Better): A Field Report
On the map: LLM reasoning → Reasoning benchmarks and evaluation
Abstract (arXiv)
This paper presents a research program dedicated to evaluating and advancing the reasoning capabilities of Bielik, a Polish large language model. The study describes a number of stages of work: initial benchmarking and creation of evaluation methodology, analyzing of comparative results with other LLMs and outlining of future prospects that take into account the limitations of the analyses conducted so far and aims to keep Bielik in the race give the ever-changing -- and competitive -- AI landscape.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 4 of its 5 references that are in the map. First posted on arXiv 11 Mar 2026.
Builds on
4 of 5 references.
References · 4
- 2024Bielik 7B v0.1: A Polish Language Model -- Development, Insights, and Evaluationcited by 15
- 2025Bielik v3 Small: Technical Reportcited by 5
- 2025Bielik 11B v2 Technical Reportcited by 2
- 2026Bielik Guard: Efficient Polish Language Safety Classifiers for LLM Content Moderationcited by 2
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- 2025Bielik 11B v3: Multilingual Large Language Model for European Languages
- 2022Towards Reasoning in Large Language Models: A Survey
- 2024LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
- 2024Can Large Language Models Act as Symbolic Reasoners?
- 2026The IOL-AI Challenge: An Open Challenge towards Advancing Linguistic Reasoning
- 2024LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models
- 2024Intelligence Analysis of Language Models
- 2025LLM-Cave: A benchmark and light environment for large language models reasoning and decision-making system