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相关论文: Making Bielik LLM Reason (Better): A Field Report

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With the emergence of advanced reasoning models like OpenAI o3 and DeepSeek-R1, large language models (LLMs) have demonstrated remarkable reasoning capabilities. However, their ability to perform rigorous logical reasoning remains an open…

人工智能 · 计算机科学 2025-02-14 Hanmeng Liu , Zhizhang Fu , Mengru Ding , Ruoxi Ning , Chaoli Zhang , Xiaozhang Liu , Yue Zhang

We introduce Bielik 7B v0.1, a 7-billion-parameter generative text model for Polish language processing. Trained on curated Polish corpora, this model addresses key challenges in language model development through innovative techniques.…

计算与语言 · 计算机科学 2026-01-01 Krzysztof Ociepa , Łukasz Flis , Krzysztof Wróbel , Adrian Gwoździej , Remigiusz Kinas

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in activities such as problem solving, decision making, and critical thinking. In recent years, large language models (LLMs) have made significant progress in…

计算与语言 · 计算机科学 2023-05-29 Jie Huang , Kevin Chen-Chuan Chang

The rapid advancements in large Language models (LLMs) have significantly enhanced their reasoning capabilities, driven by various strategies such as multi-agent collaboration. However, unlike the well-established performance improvements…

人工智能 · 计算机科学 2026-04-23 Zihan Chen , Song Wang , Zhen Tan , Xingbo Fu , Zhenyu Lei , Peng Wang , Huan Liu , Cong Shen , Jundong Li

Large Language Models (LLMs) are highly proficient in language-based tasks. Their language capabilities have positioned them at the forefront of the future AGI (Artificial General Intelligence) race. However, on closer inspection, Valmeekam…

计算与语言 · 计算机科学 2025-03-17 Dibyanayan Bandyopadhyay , Soham Bhattacharjee , Asif Ekbal

We present Bielik 11B v3, a state-of-the-art language model highly optimized for the Polish language, while also maintaining strong capabilities in other European languages. This model extends the Mistral 7B v0.2 architecture, scaled to 11B…

计算与语言 · 计算机科学 2026-01-21 Krzysztof Ociepa , Łukasz Flis , Remigiusz Kinas , Krzysztof Wróbel , Adrian Gwoździej

Large language models (LLMs) have recently shown remarkable performance in language tasks and beyond. However, due to their limited inherent causal reasoning ability, LLMs still face challenges in handling tasks that require robust causal…

计算与语言 · 计算机科学 2025-03-13 Xin Li , Zhuo Cai , Shoujin Wang , Kun Yu , Fang Chen

Large language models (LLMs), a recent advance in deep learning and machine intelligence, have manifested astonishing capacities, now considered among the most promising for artificial general intelligence. With human-like capabilities,…

人工智能 · 计算机科学 2025-09-19 Zhilun Zhou , Jing Yi Wang , Nicholas Sukiennik , Chen Gao , Fengli Xu , Yong Li , James Evans

Large language models (LLMs) have recently shown impressive performance on tasks involving reasoning, leading to a lively debate on whether these models possess reasoning capabilities similar to humans. However, despite these successes, the…

计算与语言 · 计算机科学 2024-08-07 Philipp Mondorf , Barbara Plank

This research paper discusses the advances made in the past decade in biomedicine and Large Language Models. To understand how the advances have been made hand-in-hand with one another, the paper also discusses the integration of Natural…

计算与语言 · 计算机科学 2024-06-26 Michael Ackerman

Evaluating reasoning ability in Large Language Models (LLMs) is important for advancing artificial intelligence, as it transcends mere linguistic task performance. It involves understanding whether these models truly understand information,…

人工智能 · 计算机科学 2025-10-29 Benjamin Grando Moreira

Large Language Models (LLMs) play a central role in modern artificial intelligence, yet their development has been primarily focused on English, resulting in limited support for other languages. We present PLLuM (Polish Large Language…

计算与语言 · 计算机科学 2025-11-07 Jan Kocoń , Maciej Piasecki , Arkadiusz Janz , Teddy Ferdinan , Łukasz Radliński , Bartłomiej Koptyra , Marcin Oleksy , Stanisław Woźniak , Paweł Walkowiak , Konrad Wojtasik , Julia Moska , Tomasz Naskręt , Bartosz Walkowiak , Mateusz Gniewkowski , Kamil Szyc , Dawid Motyka , Dawid Banach , Jonatan Dalasiński , Ewa Rudnicka , Bartłomiej Alberski , Tomasz Walkowiak , Aleksander Szczęsny , Maciej Markiewicz , Tomasz Bernaś , Hubert Mazur , Kamil Żyta , Mateusz Tykierko , Grzegorz Chodak , Tomasz Kajdanowicz , Przemysław Kazienko , Agnieszka Karlińska , Karolina Seweryn , Anna Kołos , Maciej Chrabąszcz , Katarzyna Lorenc , Aleksandra Krasnodębska , Artur Wilczek , Katarzyna Dziewulska , Paula Betscher , Zofia Cieślińska , Katarzyna Kowol , Daria Mikoś , Maciej Trzciński , Dawid Krutul , Marek Kozłowski , Sławomir Dadas , Rafał Poświata , Michał Perełkiewicz , Małgorzata Grębowiec , Maciej Kazuła , Marcin Białas , Roman Roszko , Danuta Roszko , Jurgita Vaičenonienė , Andrius Utka , Paweł Levchuk , Paweł Kowalski , Irena Prawdzic-Jankowska , Maciej Ogrodniczuk , Monika Borys , Anna Bulińska , Wiktoria Gumienna , Witold Kieraś , Dorota Komosińska , Katarzyna Krasnowska-Kieraś , Łukasz Kobyliński , Martyna Lewandowska , Marek Łaziński , Mikołaj Łątkowski , Dawid Mastalerz , Beata Milewicz , Agnieszka Anna Mykowiecka , Angelika Peljak-Łapińska , Sandra Penno , Zuzanna Przybysz , Michał Rudolf , Piotr Rybak , Karolina Saputa , Aleksandra Tomaszewska , Aleksander Wawer , Marcin Woliński , Joanna Wołoszyn , Alina Wróblewska , Bartosz Żuk , Filip Żarnecki , Konrad Kaczyński , Anna Cichosz , Zuzanna Deckert , Monika Garnys , Izabela Grabarczyk , Wojciech Janowski , Sylwia Karasińska , Aleksandra Kujawiak , Piotr Misztela , Maria Szymańska , Karolina Walkusz , Igor Siek , Jakub Kwiatkowski , Piotr Pęzik

Recent advancements in Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains. However, effective decision-making relies heavily on strong reasoning abilities. Reasoning is the foundation for…

Large Language Models (LLMs) excel in generating personalized content and facilitating interactive dialogues, showcasing their remarkable aptitude for a myriad of applications. However, their capabilities in reasoning and providing…

计算与语言 · 计算机科学 2024-02-16 Min Zhang , Sato Takumi , Jack Zhang , Jun Wang

We introduce Bielik v3, a series of parameter-efficient generative text models (1.5B and 4.5B) optimized for Polish language processing. These models demonstrate that smaller, well-optimized architectures can achieve performance comparable…

机器学习 · 计算机科学 2025-05-12 Krzysztof Ociepa , Łukasz Flis , Remigiusz Kinas , Krzysztof Wróbel , Adrian Gwoździej

Achieving human-level intelligence requires refining the transition from the fast, intuitive System 1 to the slower, more deliberate System 2 reasoning. While System 1 excels in quick, heuristic decisions, System 2 relies on logical…

Large Language Models (LLMs) have succeeded remarkably in various natural language processing (NLP) tasks, yet their reasoning capabilities remain a fundamental challenge. While LLMs exhibit impressive fluency and factual recall, their…

计算与语言 · 计算机科学 2025-05-29 Avinash Patil , Aryan Jadon

While large language models (LLMs) have demonstrated impressive capabilities across various natural language processing tasks by acquiring rich factual knowledge from their broad training data, their ability to synthesize and logically…

计算与语言 · 计算机科学 2024-07-31 Tianshi Zheng , Jiaxin Bai , Yicheng Wang , Tianqing Fang , Yue Guo , Yauwai Yim , Yangqiu Song

Reasoning is a fundamental cognitive process that enables logical inference, problem-solving, and decision-making. With the rapid advancement of large language models (LLMs), reasoning has emerged as a key capability that distinguishes…

Mathematical reasoning has long represented one of the most fundamental and challenging frontiers in artificial intelligence research. In recent years, large language models (LLMs) have achieved significant advances in this area. This…

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