Search Results for author: Barbara Rychalska

Found 16 papers, 7 papers with code

Synerise at RecSys 2021: Twitter user engagement prediction with a fast neural model

1 code implementation23 Sep 2021 Michał Daniluk, Jacek Dąbrowski, Barbara Rychalska, Konrad Gołuchowski

Each data point contains multiple sources of information, such as tweet text along with engagement features, user features, and tweet features.

Feature Engineering

Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations

1 code implementation21 Jun 2021 Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki, Michał Górszczak, Barbara Rychalska, Koryna Lewandowska, Tomasz Trzciński, Bartosz Zieliński

Motivated by this observation, we introduce a novel visual probing framework for explaining the self-supervised models by leveraging probing tasks employed previously in natural language processing.

Representation Learning

T-EMDE: Sketching-based global similarity for cross-modal retrieval

no code implementations10 May 2021 Barbara Rychalska, Mikolaj Wieczorek, Jacek Dabrowski

However, each modality embeddings stem from non-related feature spaces, which causes the notorious 'heterogeneity gap'.

Cross-Modal Retrieval Recommendation Systems +1

Modeling Multi-Destination Trips with Sketch-Based Model

1 code implementation22 Feb 2021 Michał Daniluk, Barbara Rychalska, Konrad Gołuchowski, Jacek Dąbrowski

The recently proposed EMDE (Efficient Manifold Density Estimator) model achieves state of-the-art results in session-based recommendation.

Graph Embedding Session-Based Recommendations

DiP Benchmark Tests: Evaluation Benchmarks for Discourse Phenomena in MT

no code implementations1 Jan 2021 Prathyusha Jwalapuram, Barbara Rychalska, Shafiq Joty, Dominika Basaj

Despite increasing instances of machine translation (MT) systems including extrasentential context information, the evidence for translation quality improvement is sparse, especially for discourse phenomena.

Machine Translation Translation

Multi-modal Embedding Fusion-based Recommender

no code implementations13 May 2020 Anna Wroblewska, Jacek Dabrowski, Michal Pastuszak, Andrzej Michalowski, Michal Daniluk, Barbara Rychalska, Mikolaj Wieczorek, Sylwia Sysko-Romanczuk

Contrary to existing recommendation systems, our platform supports multiple types of interaction data with multiple modalities of metadata natively.

Recommendation Systems

Can Your Context-Aware MT System Pass the DiP Benchmark Tests? : Evaluation Benchmarks for Discourse Phenomena in Machine Translation

no code implementations30 Apr 2020 Prathyusha Jwalapuram, Barbara Rychalska, Shafiq Joty, Dominika Basaj

Despite increasing instances of machine translation (MT) systems including contextual information, the evidence for translation quality improvement is sparse, especially for discourse phenomena.

Machine Translation Translation

How much should you ask? On the question structure in QA systems.

no code implementations WS 2018 Barbara Rychalska, Dominika Basaj, Anna Wr{\'o}blewska, Przemyslaw Biecek

Datasets that boosted state-of-the-art solutions for Question Answering (QA) systems prove that it is possible to ask questions in natural language manner.

Question Answering

How much should you ask? On the question structure in QA systems

no code implementations11 Sep 2018 Dominika Basaj, Barbara Rychalska, Przemyslaw Biecek, Anna Wroblewska

Datasets that boosted state-of-the-art solutions for Question Answering (QA) systems prove that it is possible to ask questions in natural language manner.

Question Answering

Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System

no code implementations WS 2018 Barbara Rychalska, Dominika Basaj, Przemyslaw Biecek, Anna Wroblewska

In this paper we present the results of an investigation of the importance of verbs in a deep learning QA system trained on SQuAD dataset.

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