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ORCIDBarbara Rychalska
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2020 – today
- 2023
[j1]Witold Oleszkiewicz
, Dominika Basaj, Igor Sieradzki, Michal Górszczak, Barbara Rychalska, Koryna Lewandowska, Tomasz Trzcinski, Bartosz Zielinski:
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations. IEEE Access 11: 13028-13043 (2023)- [c16]Barbara Rychalska, Igor Sieradzki, Jacek Dabrowski:
The Monad Platform - Temporal Aspects in Behavioral Modeling. ECAI 2023: 3226-3232 - [c15]Barbara Rychalska, Szymon Lukasik, Jacek Dabrowski:
Synerise Monad: A Foundation Model for Behavioral Event Data. SIGIR 2023: 3344-3348 - [i14]Gergely Stomfai, Lukasz Sienkiewicz, Barbara Rychalska:
Multidimensional Hopfield Networks for clustering. CoRR abs/2310.07239 (2023) - 2022
- [c14]Jacek Dabrowski, Barbara Rychalska:
Synerise Monad - Real-Time Multimodal Behavioral Modeling. CIKM 2022: 5083-5084 - [c13]Piotr Andruszkiewicz, Barbara Rychalska:
Vanilla Recurrent Neural Networks for Interpretable Semantic Textual Similarity. PACLIC 2022: 703-712 - 2021
- [c12]Mikolaj Wieczorek, Barbara Rychalska, Jacek Dabrowski:
On the Unreasonable Effectiveness of Centroids in Image Retrieval. ICONIP (4) 2021: 212-223 - [c11]Jacek Dabrowski, Barbara Rychalska, Michal Daniluk, Dominika Basaj, Konrad Goluchowski, Piotr Babel, Andrzej Michalowski, Adam Jakubowski:
An Efficient Manifold Density Estimator for All Recommendation Systems. ICONIP (4) 2021: 323-337 - [c10]Barbara Rychalska, Piotr Babel, Konrad Goluchowski, Andrzej Michalowski, Jacek Dabrowski, Przemyslaw Biecek:
Cleora: A Simple, Strong and Scalable Graph Embedding Scheme. ICONIP (4) 2021: 338-352 - [c9]Dominika Basaj, Witold Oleszkiewicz, Igor Sieradzki, Michal Górszczak, Barbara Rychalska, Tomasz Trzcinski, Bartosz Zielinski:
Explaining Self-Supervised Image Representations with Visual Probing. IJCAI 2021: 592-598 - [c8]Michal Daniluk, Jacek Dabrowski, Barbara Rychalska, Konrad Goluchowski:
Synerise at RecSys 2021: Twitter user engagement prediction with a fast neural model. RecSys Challenge 2021: 15-21 - [c7]Michal Daniluk, Barbara Rychalska, Konrad Goluchowski, Jacek Dabrowski:
Modeling Multi-Destination Trips with Sketch-Based Model. WebTour@WSDM 2021: 29-33 - [i13]Barbara Rychalska, Piotr Babel, Konrad Goluchowski, Andrzej Michalowski, Jacek Dabrowski:
Cleora: A Simple, Strong and Scalable Graph Embedding Scheme. CoRR abs/2102.02302 (2021) - [i12]Michal Daniluk, Barbara Rychalska, Konrad Goluchowski, Jacek Dabrowski:
Modeling Multi-Destination Trips with Sketch-Based Model. CoRR abs/2102.11252 (2021) - [i11]Mikolaj Wieczorek, Barbara Rychalska, Jacek Dabrowski:
On the Unreasonable Effectiveness of Centroids in Image Retrieval. CoRR abs/2104.13643 (2021) - [i10]Barbara Rychalska, Mikolaj Wieczorek, Jacek Dabrowski:
T-EMDE: Sketching-based global similarity for cross-modal retrieval. CoRR abs/2105.04242 (2021) - [i9]Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki, Michal Górszczak, Barbara Rychalska, Koryna Lewandowska, Tomasz Trzcinski, Bartosz Zielinski:
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations. CoRR abs/2106.11054 (2021) - [i8]Michal Daniluk, Jacek Dabrowski, Barbara Rychalska, Konrad Goluchowski:
Synerise at RecSys 2021: Twitter user engagement prediction with a fast neural model. CoRR abs/2109.12985 (2021) - 2020
- [i7]Prathyusha Jwalapuram, Barbara Rychalska, Shafiq R. Joty, Dominika Basaj:
Can Your Context-Aware MT System Pass the DiP Benchmark Tests? : Evaluation Benchmarks for Discourse Phenomena in Machine Translation. CoRR abs/2004.14607 (2020) - [i6]Anna Wróblewska, Jacek Dabrowski, Michal Pastuszak, Andrzej Michalowski, Michal Daniluk, Barbara Rychalska, Mikolaj Wieczorek, Sylwia Sysko-Romanczuk:
Multi-modal Embedding Fusion-based Recommender. CoRR abs/2005.06331 (2020) - [i5]Jacek Dabrowski, Barbara Rychalska, Michal Daniluk, Dominika Basaj, Konrad Goluchowski, Piotr Babel, Andrzej Michalowski:
An efficient manifold density estimator for all recommendation systems. CoRR abs/2006.01894 (2020) - [i4]Barbara Rychalska, Dominika Basaj, Jacek Dabrowski, Michal Daniluk:
I know why you like this movie: Interpretable Efficient Multimodal Recommender. CoRR abs/2006.09979 (2020)
2010 – 2019
- 2019
- [c6]Barbara Rychalska, Dominika Basaj, Alicja Gosiewska, Przemyslaw Biecek:
Models in the Wild: On Corruption Robustness of Neural NLP Systems. ICONIP (3) 2019: 235-247 - [p1]Krystyna Chodorowska, Barbara Rychalska, Katarzyna Pakulska, Piotr Andruszkiewicz:
To Improve, or Not to Improve; How Changes in Corpora Influence the Results of Machine Learning Tasks on the Example of Datasets Used for Paraphrase Identification. Intelligent Methods and Big Data in Industrial Applications 2019: 353-366 - 2018
- [c5]Barbara Rychalska, Dominika Basaj, Anna Wróblewska, Przemyslaw Biecek:
How much should you ask? On the question structure in QA systems. BlackboxNLP@EMNLP 2018: 319-321 - [c4]Barbara Rychalska, Dominika Basaj, Anna Wróblewska, Przemyslaw Biecek:
Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System. BlackboxNLP@EMNLP 2018: 322-324 - [c3]Barbara Rychalska, Helena T. Glabska, Anna Wróblewska:
Multi-Intent Hierarchical Natural Language Understanding for Chatbots. SNAMS 2018: 256-259 - [c2]Dominika Basaj, Barbara Rychalska, Anna Wróblewska:
LAS: Language Agnostic System for Question Answering. SNAMS 2018: 260-263 - [i3]Dominika Basaj, Barbara Rychalska, Przemyslaw Biecek, Anna Wróblewska:
How much should you ask? On the question structure in QA systems. CoRR abs/1809.03734 (2018) - [i2]Barbara Rychalska, Dominika Basaj, Przemyslaw Biecek, Anna Wróblewska:
Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System. CoRR abs/1809.03740 (2018) - [i1]Barbara Rychalska, Dominika Basaj, Przemyslaw Biecek:
Are you tough enough? Framework for Robustness Validation of Machine Comprehension Systems. CoRR abs/1812.02205 (2018) - 2016
- [c1]Barbara Rychalska, Katarzyna Pakulska, Krystyna Chodorowska, Wojciech Walczak, Piotr Andruszkiewicz:
Samsung Poland NLP Team at SemEval-2016 Task 1: Necessity for diversity; combining recursive autoencoders, WordNet and ensemble methods to measure semantic similarity. SemEval@NAACL-HLT 2016: 602-608
Coauthor Index
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