activity
20202026
most citedA Review of Platforms for the Development of Agent Systems

32 citations · 115 across the 29 of their papers we have counts for

collaborators

29 papers

cs.RO2026

Semantic Radiance Fields as Simulators for Spatial Reasoning in Real-World Scenes

Nico Heider, Michał Jan Włodarczyk, Katarzyna Wasielewska-Michniewska +5

Training and evaluating spatial reasoning in embodied agents requires diverse environments that are both geometrically faithful and semantically queryable. Synthetic simulators off…

cs.CL2026

Clickbait detection: quick inference with maximum impact

Soveatin Kuntur, Panggih Kusuma Ningrum, Anna Wróblewska +2

We propose a lightweight hybrid approach to clickbait detection that combines OpenAI semantic embeddings with six compact heuristic features capturing stylistic and informational c…

cs.CL2026

Graph Neural Networks for Misinformation Detection: Performance-Efficiency Trade-offs

Soveatin Kuntur, Maciej Krzywda, Anna Wróblewska +4

The rapid spread of online misinformation has led to increasingly complex detection models, including large language models and hybrid architectures. However, their computational c…

cs.MA2025

EnergyTwin: A Multi-Agent System for Simulating and Coordinating Energy Microgrids

Jakub Muszyński, Ignacy Walużenicz, Patryk Zan +4

Microgrids are deployed to reduce purchased grid energy, limit exposure to volatile tariffs, and ensure service continuity during disturbances. This requires coordinating heterogen…

cs.MA2025

Contemporary Agent Technology: LLM-Driven Advancements vs Classic Multi-Agent Systems

Costin Bădică, Amelia Bădică, Maria Ganzha +4

This contribution provides our comprehensive reflection on the contemporary agent technology, with a particular focus on the advancements driven by Large Language Models (LLM) vs c…

cs.CL2025★ 1 cited

Applying Text Mining to Analyze Human Question Asking in Creativity Research

Anna Wróblewska, Marceli Korbin, Yoed N. Kenett +3

Creativity relates to the ability to generate novel and effective ideas in the areas of interest. How are such creative ideas generated? One possible mechanism that supports creati…

cs.DB2024

Realizing a Collaborative RDF Benchmark Suite in Practice

Piotr Sowinski, Maria Ganzha

Collaborative mechanisms allow benchmarks to be updated continuously and adjust to the changing requirements and new use cases. This paradigm is employed for example in the field o…

cs.SE2024

Overview of Current Challenges in Multi-Architecture Software Engineering and a Vision for the Future

Piotr Sowinski, Ignacio Lacalle, Rafael Vano +3

The landscape of computing technologies is changing rapidly, straining existing software engineering practices and tools. The growing need to produce and maintain increasingly comp…

cs.LG2024

Adaptive Active Inference Agents for Heterogeneous and Lifelong Federated Learning

Anastasiya Danilenka, Alireza Furutanpey, Victor Casamayor Pujol +5

Handling heterogeneity and unpredictability are two core problems in pervasive computing. The challenge is to seamlessly integrate devices with varying computational resources in a…

cs.CL2024★ 7 cited

Fake News Detection: It's All in the Data!

Soveatin Kuntur, Anna Wróblewska, Marcin Paprzycki +1

This comprehensive survey serves as an indispensable resource for researchers embarking on the journey of fake news detection. By highlighting the pivotal role of dataset quality a…

cs.DB2024

Not All RDF is Created Equal: Investigating RDF Load Times on Resource-Constrained Devices

Piotr Sowinski, Anh Le-Tuan, Pawel Szmeja +1

As the role of knowledge-based systems in IoT keeps growing, ensuring resource efficiency of RDF stores becomes critical. However, up until now benchmarks of RDF stores were most o…

cs.DB2023

RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and Practice

Piotr Sowinski, Pawel Szmeja, Maria Ganzha +1

Over the years, RDF streaming was explored in research and practice from many angles, resulting in a wide range of RDF stream definitions. This variety presents a major challenge i…

cs.CL2023★ 2 cited

Enriching language models with graph-based context information to better understand textual data

Albert Roethel, Maria Ganzha, Anna Wróblewska

A considerable number of texts encountered daily are somehow connected with each other. For example, Wikipedia articles refer to other articles via hyperlinks, scientific papers re…

cs.DB2023

RiverBench: an Open RDF Streaming Benchmark Suite

Piotr Sowinski, Maria Ganzha, Marcin Paprzycki

RDF streaming has been explored by the Semantic Web community from many angles, resulting in multiple task formulations and streaming methods. However, for many existing formulatio…

cs.NI2023★ 6 cited

Application of genetic algorithm to load balancing in networks with a homogeneous traffic flow

Marek Bolanowski, Alicja Gerka, Andrzej Paszkiewicz +2

The concept of extended cloud requires efficient network infrastructure to support ecosystems reaching form the edge to the cloud(s). Standard approaches to network load balancing…

cs.CV2023★ 2 cited

Towards Edge-Cloud Architectures for Personal Protective Equipment Detection

Jaroslaw Legierski, Kajetan Rachwal, Piotr Sowinski +5

Detecting Personal Protective Equipment in images and video streams is a relevant problem in ensuring the safety of construction workers. In this contribution, an architecture enab…

cs.PF2022★ 19 cited

Eficiency of REST and gRPC realizing communication tasks in microservice-based ecosystems

Marek Bolanowski, Kamil Żak, Andrzej Paszkiewicz +5

The aim of this contribution is to analyse practical aspects of the use of REST APIs and gRPC to realize communication tasks in applications in microservice-based ecosystems. On th…

cs.LG2022★ 3 cited

Introducing Federated Learning into Internet of Things ecosystems -- preliminary considerations

Karolina Bogacka, Katarzyna Wasielewska-Michniewska, Marcin Paprzycki +4

Federated learning (FL) was proposed to facilitate the training of models in a distributed environment. It supports the protection of (local) data privacy and uses local resources…

cs.DB2022★ 5 cited

Efficient RDF Streaming for the Edge-Cloud Continuum

Piotr Sowinski, Katarzyna Wasielewska-Michniewska, Maria Ganzha +3

With the ongoing, gradual shift of large-scale distributed systems towards the edge-cloud continuum, the need arises for software solutions that are universal, scalable, practical,…

cs.LG2022

StatMix: Data augmentation method that relies on image statistics in federated learning

Dominik Lewy, Jacek Mańdziuk, Maria Ganzha +1

Availability of large amount of annotated data is one of the pillars of deep learning success. Although numerous big datasets have been made available for research, this is often n…

cs.LG2022★ 2 cited

Using adversarial images to improve outcomes of federated learning for non-IID data

Anastasiya Danilenka, Maria Ganzha, Marcin Paprzycki +1

One of the important problems in federated learning is how to deal with unbalanced data. This contribution introduces a novel technique designed to deal with label skewed non-IID d…

cs.SE2022★ 7 cited

Ontology Reuse: the Real Test of Ontological Design

Piotr Sowinski, Katarzyna Wasielewska-Michniewska, Maria Ganzha +2

Reusing ontologies in practice is still very challenging, especially when multiple ontologies are (jointly) involved. Moreover, despite recent advances, the realization of systemat…

cs.NI2022★ 6 cited

An Energy Aware Clustering Scheme for 5G-enabled Edge Computing based IoMT Framework

Jitendra Kumar Samriya, Mohit Kumar, Maria Ganzha +3

In recent years, 5G network systems start to offer communication infrastructure for Internet of Things (IoT) applications, especially for health care service pro-viders. In smart h…

cs.LG2022★ 1 cited

Applying machine learning to predict behavior of bus transport in Warsaw, Poland

Łukasz Pałys, Maria Ganzha, Marcin Paprzycki

Nowadays, it is possible to collect precise data describing movements of public transport. Specifically, for each bus (or tram) geoposition data can be regularly collected. This in…