Search Results for author: Anna Wróblewska

Found 17 papers, 2 papers with code

Named Entity Recognition -- Is there a glass ceiling?

1 code implementation6 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.

named-entity-recognition Named Entity Recognition +1

Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout

no code implementations4 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.

named-entity-recognition Named Entity Recognition +2

Polish Natural Language Inference and Factivity -- an Expert-based Dataset and Benchmarks

no code implementations10 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.

Natural Language Inference Negation

Automatic Language Identification for Celtic Texts

no code implementations9 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.

Language Identification

Multilingual Transformers for Product Matching -- Experiments and a New Benchmark in Polish

no code implementations31 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.

Does a Technique for Building Multimodal Representation Matter? -- Comparative Analysis

no code implementations9 Jun 2022 Maciej Pawłowski, Anna Wróblewska, Sylwia Sysko-Romańczuk

Experiments are conducted on three datasets: Amazon Reviews, MovieLens25M, and MovieLens1M datasets.

Identifying Substitute and Complementary Products for Assortment Optimization with Cleora Embeddings

no code implementations10 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.

Graph Embedding Marketing

Revisiting Distance Metric Learning for Few-Shot Natural Language Classification

no code implementations28 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.

Few-Shot Learning Language Modelling +1

Distance Metric Learning Loss Functions in Few-Shot Scenarios of Supervised Language Models Fine-Tuning

no code implementations28 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.

Metric Learning

Automating the Analysis of Institutional Design in International Agreements

no code implementations26 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.

Improving Object Detection Quality in Football Through Super-Resolution Techniques

no code implementations31 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.

Object object-detection +3

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