4 papers
Tackling prediction tasks in relational databases with LLMs
Marek Wydmuch, Åukasz Borchmann, Filip GraliÅski
Though large language models (LLMs) have demonstrated exceptional performance across numerous problems, their application to predictive tasks in relational databases remains largel…
Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists
MichaÅ Pietruszka, Åukasz Borchmann, Aleksander JÄdrosz +1
We present a benchmark for large language models designed to tackle one of the most knowledge-intensive tasks in data science: writing feature engineering code, which requires doma…
Dynamic Boundary Time Warping for Sub-sequence Matching with Few Examples
Åukasz Borchmann, Dawid Jurkiewicz, Filip GraliÅski +1
The paper presents a novel method of finding a fragment in a long temporal sequence similar to the set of shorter sequences. We are the first to propose an algorithm for such a sea…
Arctic-TILT. Business Document Understanding at Sub-Billion Scale
Åukasz Borchmann, MichaÅ Pietruszka, Wojciech JaÅkowski +13
The vast portion of workloads employing LLMs involves answering questions grounded on PDF or scan content. We introduce the Arctic-TILT achieving accuracy on par with models 1000$\…