no code implementations • 31 Jan 2024 • Karolina Seweryn, Gabriel Chęć, Szymon Łukasik, Anna Wróblewska
The study contributes to the growing field of sports technology by demonstrating the practical benefits and limitations of integrating super-resolution techniques in football analytics and broadcasting.
no code implementations • 21 Sep 2023 • Karolina Seweryn, Anna Wróblewska, Szymon Łukasik
Overall, this survey provides a valuable resource for researchers interested in the field of action scene understanding in soccer.
no code implementations • 26 May 2023 • Anna Wróblewska, Bartosz Pieliński, Karolina Seweryn, Sylwia Sysko-Romańczuk, Karol Saputa, Aleksandra Wichrowska, Hanna Schreiber
This paper explores the automatic knowledge extraction of formal institutional design - norms, rules, and actors - from international agreements.
1 code implementation • 10 May 2023 • Albert Roethel, Maria Ganzha, Anna Wróblewska
A considerable number of texts encountered daily are somehow connected with each other.
no code implementations • 28 Nov 2022 • Witold Sosnowski, Anna Wróblewska, Karolina Seweryn, Piotr Gawrysiak
Our systematic experiments have shown that under few-shot learning settings, particularly proxy-based DML losses can positively affect the fine-tuning and inference of a supervised language model.
no code implementations • 28 Nov 2022 • Witold Sosnowski, Karolina Seweryn, Anna Wróblewska, Piotr Gawrysiak
This paper presents an analysis regarding an influence of the Distance Metric Learning (DML) loss functions on the supervised fine-tuning of the language models for classification tasks.
no code implementations • 2 Sep 2022 • Anna Wróblewska, Bartosz Pieliński, Karolina Seweryn, Karol Saputa, Aleksandra Wichrowska, Sylwia Sysko-Romańczuk, Hanna Schreiber
This paper presents research on a prototype developed to serve the quantitative study of public policy design.
no code implementations • 10 Aug 2022 • Sergiy Tkachuk, Anna Wróblewska, Jacek Dąbrowski, Szymon Łukasik
Recent years brought an increasing interest in the application of machine learning algorithms in e-commerce, omnichannel marketing, and the sales industry.
no code implementations • 9 Jun 2022 • Maciej Pawłowski, Anna Wróblewska, Sylwia Sysko-Romańczuk
Experiments are conducted on three datasets: Amazon Reviews, MovieLens25M, and MovieLens1M datasets.
no code implementations • 31 May 2022 • Michał Możdżonek, Anna Wróblewska, Sergiy Tkachuk, Szymon Łukasik
We tested multilingual mBERT and XLM-RoBERTa models in English on Web Data Commons - training dataset and gold standard for large-scale product matching.
no code implementations • 9 Mar 2022 • Olha Dovbnia, Anna Wróblewska
This work's main goals were: (1) to collect the dataset of three Celtic languages; (2) to prepare a method to identify the languages from the Celtic family, i. e. to train a successful classification model; (3) to evaluate the influence of different feature extraction methods, and explore the applicability of the unsupervised models as a feature extraction technique; (4) to experiment with the unsupervised feature extraction on a reduced annotated set.
no code implementations • 10 Jan 2022 • Daniel Ziembicki, Anna Wróblewska, Karolina Seweryn
The dataset contains entirely natural language utterances in Polish and gathers 2, 432 verb-complement pairs and 309 unique verbs.
no code implementations • 24 Dec 2021 • Anna Wróblewska, Paweł Rzepiński, Sylwia Sysko-Romańczuk
This paper presents our research regarding spoiler detection in reviews.
no code implementations • 4 Oct 2021 • Weronika Łajewska, Anna Wróblewska
We prepared a method for person entity linkage (named entity recognition and disambiguation) and new testing datasets.
no code implementations • 12 May 2021 • Tomasz Stanisławek, Filip Graliński, Anna Wróblewska, Dawid Lipiński, Agnieszka Kaliska, Paulina Rosalska, Bartosz Topolski, Przemysław Biecek
The relevance of the Key Information Extraction (KIE) task is increasingly important in natural language processing problems.
no code implementations • 4 Mar 2020 • Filip Graliński, Tomasz Stanisławek, Anna Wróblewska, Dawid Lipiński, Agnieszka Kaliska, Paulina Rosalska, Bartosz Topolski, Przemysław Biecek
State-of-the-art solutions for Natural Language Processing (NLP) are able to capture a broad range of contexts, like the sentence-level context or document-level context for short documents.
1 code implementation • 6 Oct 2019 • Tomasz Stanislawek, Anna Wróblewska, Alicja Wójcicka, Daniel Ziembicki, Przemyslaw Biecek
A new enriched semantic annotation of errors for this data set and new diagnostic data sets are attached in the supplementary materials.