4 citations · 7 across the 9 of their papers we have counts for
11 papers
Dynamics of low energy wave packets in the one-dimensional quantum Heisenberg ferromagnet
Mateusz Kwaśnicki, Marcin Napiórkowski, Sören Petrat +1
Spin wave theory plays a central role in the analysis of low-energy properties of the quantum ferromagnetic Heisenberg model. In this work, we present a first step towards a rigoro…
Shieldstral
Antonia Calvi, Avinash Sooriyarachchi, Giada Pistilli +273
We introduce Shieldstral, a 3B-parameter policy-adaptive multimodal safety classifier that matches or outperforms models nearly 7 its size on text safety benchmarks and set…
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…
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$\…
Document Understanding Dataset and Evaluation (DUDE)
Jordy Van Landeghem, Rubén Tito, Łukasz Borchmann +10
We call on the Document AI (DocAI) community to reevaluate current methodologies and embrace the challenge of creating more practically-oriented benchmarks. Document Understanding…
STable: Table Generation Framework for Encoder-Decoder Models
Michał Pietruszka, Michał Turski, Łukasz Borchmann +5
The output structure of database-like tables, consisting of values structured in horizontal rows and vertical columns identifiable by name, can cover a wide range of NLP tasks. Fol…
Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer
Rafał Powalski, Łukasz Borchmann, Dawid Jurkiewicz +3
We address the challenging problem of Natural Language Comprehension beyond plain-text documents by introducing the TILT neural network architecture which simultaneously learns lay…
From Dataset Recycling to Multi-Property Extraction and Beyond
Tomasz Dwojak, Michał Pietruszka, Łukasz Borchmann +2
This paper investigates various Transformer architectures on the WikiReading Information Extraction and Machine Reading Comprehension dataset. The proposed dual-source model outper…
Successive Halving Top-k Operator
Michał Pietruszka, Łukasz Borchmann, Filip Graliński
We propose a differentiable successive halving method of relaxing the top-k operator, rendering gradient-based optimization possible. The need to perform softmax iteratively on the…
Sparsifying Transformer Models with Trainable Representation Pooling
Michał Pietruszka, Łukasz Borchmann, Łukasz Garncarek
We propose a novel method to sparsify attention in the Transformer model by learning to select the most-informative token representations during the training process, thus focusing…
On the Multi-Property Extraction and Beyond
Tomasz Dwojak, Michał Pietruszka, Łukasz Borchmann +2
In this paper, we investigate the Dual-source Transformer architecture on the WikiReading information extraction and machine reading comprehension dataset. The proposed model outpe…