5 citations · 15 across the 7 of their papers we have counts for
8 papers
Domain Adaptation of Foundation LLMs for e-Commerce
Christian Herold, Michael Kozielski, Tala Bazazo +6
We present the e-Llama models: 8 billion and 70 billion parameter large language models that are adapted towards the e-commerce domain. These models are meant as foundation models…
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations
Witold Oleszkiewicz, Dominika Basaj, Igor Sieradzki +5
Recently introduced self-supervised methods for image representation learning provide on par or superior results to their fully supervised competitors, yet the corresponding effort…
I know why you like this movie: Interpretable Efficient Multimodal Recommender
Barbara Rychalska, Dominika Basaj, Jacek Dąbrowski +1
Recently, the Efficient Manifold Density Estimator (EMDE) model has been introduced. The model exploits Local Sensitive Hashing and Count-Min Sketch algorithms, combining them with…
An efficient manifold density estimator for all recommendation systems
Jacek Dąbrowski, Barbara Rychalska, Michał Daniluk +5
Many unsupervised representation learning methods belong to the class of similarity learning models. While various modality-specific approaches exist for different types of data, a…
Can Your Context-Aware MT System Pass the DiP Benchmark Tests? : Evaluation Benchmarks for Discourse Phenomena in Machine Translation
Prathyusha Jwalapuram, Barbara Rychalska, Shafiq Joty +1
Despite increasing instances of machine translation (MT) systems including contextual information, the evidence for translation quality improvement is sparse, especially for discou…
Are you tough enough? Framework for Robustness Validation of Machine Comprehension Systems
Barbara Rychalska, Dominika Basaj, Przemyslaw Biecek
Deep Learning NLP domain lacks procedures for the analysis of model robustness. In this paper we propose a framework which validates robustness of any Question Answering model thro…
Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System
Barbara Rychalska, Dominika Basaj, Przemyslaw Biecek +1
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. We show that main verbs in questions carr…
How much should you ask? On the question structure in QA systems
Dominika Basaj, Barbara Rychalska, Przemyslaw Biecek +1
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. However, users are still…