7 citations · 12 across the 7 of their papers we have counts for
7 papers
OmicsLM: A Multimodal Large Language Model for Multi-Sample Omics Reasoning
Maciej Sypetkowski, Joanna Krawczyk, Łukasz Smoliński +4
Interpreting transcriptomic data is one of the most common analytical tasks in modern biology. Yet most current models either consume expression profiles without producing natural-…
BioResearcher: Scenario-Guided Multi-Agent for Translational Medicine
Remigiusz Kinas, Joanna Krawczyk, Rafał Powalski +6
Translational medicine turns underspecified development goals into evidence synthesis that must combine literature, trials, patents, and quantitative multi-omics analysis while pre…
RapidDock: Unlocking Proteome-scale Molecular Docking
Rafał Powalski, Bazyli Klockiewicz, Maciej Jaśkowski +6
Accelerating molecular docking -- the process of predicting how molecules bind to protein targets -- could boost small-molecule drug discovery and revolutionize medicine. Unfortuna…
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…
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…
UniCase -- Rethinking Casing in Language Models
Rafal Powalski, Tomasz Stanislawek
In this paper, we introduce a new approach to dealing with the problem of case-sensitiveness in Language Modelling (LM). We propose simple architecture modification to the RoBERTa…
LAMBERT: Layout-Aware (Language) Modeling for information extraction
Łukasz Garncarek, Rafał Powalski, Tomasz Stanisławek +4
We introduce a simple new approach to the problem of understanding documents where non-trivial layout influences the local semantics. To this end, we modify the Transformer encoder…