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Łukasz Borchmann

Applica.ai

13 papers hereh-index 8521 citations22 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author10

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CL9
  • cs.LG2
  • cs.CV1
  • cs.DS1
affiliations
  • Applica.ai

identity via Semantic Scholar / OpenAlex

activity
20192024
most citedSTable: Table Generation Framework for Encoder-Decoder Models

4 citations · 7 across the 10 of their papers we have counts for

collaborators
Showing 2024Show all

3 papers · 1 filter

cs.LG2024

Tackling prediction tasks in relational databases with LLMs

Marek Wydmuch, Łukasz Borchmann, Filip Graliński

Though large language models (LLMs) have demonstrated exceptional performance across numerous problems, their application to predictive tasks in relational databases remains largel…

cs.CL2024

Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists

Michał Pietruszka, Łukasz Borchmann, Aleksander Jędrosz +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…

cs.CL2024

Arctic-TILT. Business Document Understanding at Sub-Billion Scale

Łukasz Borchmann, Michał Pietruszka, Wojciech Jaśkowski +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$\…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.