34 citations · 84 across the 10 of their papers we have counts for
15 papers
GeoLEON-CLIP: Graph-Anchored Multimodal Contrastive Learning for Geographic Region Representation
Radoslaw Malek, Szymon Soltysiak, Aleksandra Kawala-Sterniuk +1
Geographic regions are multimodal: satellite imagery captures visual morphology, text conveys human-interpretable semantics, and map structures describe urban context. Existing geo…
From a Large-Scale Teacher to Efficient Multimodal Students for Search Relevance Prediction
Tomasz Gniazdowski, Mohammadreza Momenifar, Nadia Vase +6
Relevance prediction between user queries and items is a fundamental component of e-commerce search systems. Traditionally, high-quality relevance labels are obtained through human…
LEON: Location Embeddings from OSM Neighborhoods via Hexagonal Graph Masked Autoencoders
Szymon Soltysiak, Radoslaw Malek, Jedrzej Kusnierz +3
Geographic information systems increasingly rely on sophisticated spatial representation learning techniques to extract meaningful patterns from complex geospatial data. This paper…
OBSR: Open Benchmark for Spatial Representations
Julia Moska, Oleksii Furman, Kacper Kozaczko +4
GeoAI is evolving rapidly, fueled by diverse geospatial datasets like traffic patterns, environmental data, and crowdsourced OpenStreetMap (OSM) information. While sophisticated AI…
A Vision for Geo-Temporal Deep Research Systems: Towards Comprehensive, Transparent, and Reproducible Geo-Temporal Information Synthesis
Bruno Martins, Piotr Szymański, Piotr Gramacki
The emergence of Large Language Models (LLMs) has transformed information access, with current LLMs also powering deep research systems that can generate comprehensive report-style…
Evaluation of Code LLMs on Geospatial Code Generation
Piotr Gramacki, Bruno Martins, Piotr Szymański
Software development support tools have been studied for a long time, with recent approaches using Large Language Models (LLMs) for code generation. These models can generate Pytho…
SRAI: Towards Standardization of Geospatial AI
Piotr Gramacki, Kacper Leśniara, Kamil Raczycki +3
Spatial Representations for Artificial Intelligence (srai) is a Python library for working with geospatial data. The library can download geospatial data, split a given area into m…
Improved DeepFake Detection Using Whisper Features
Piotr Kawa, Marcin Plata, Michał Czuba +2
With a recent influx of voice generation methods, the threat introduced by audio DeepFake (DF) is ever-increasing. Several different detection methods have been presented as a coun…
This is the way: designing and compiling LEPISZCZE, a comprehensive NLP benchmark for Polish
Łukasz Augustyniak, Kamil Tagowski, Albert Sawczyn +9
The availability of compute and data to train larger and larger language models increases the demand for robust methods of benchmarking the true progress of LM training. Recent yea…
gtfs2vec -- Learning GTFS Embeddings for comparing Public Transport Offer in Microregions
Piotr Gramacki, Szymon Woźniak, Piotr Szymański
We selected 48 European cities and gathered their public transport timetables in the GTFS format. We utilized Uber's H3 spatial index to divide each city into hexagonal micro-regio…
Transfer Learning Approach to Bicycle-sharing Systems' Station Location Planning using OpenStreetMap Data
Kamil Raczycki, Piotr Szymański
Bicycle-sharing systems (BSS) have become a daily reality for many citizens of larger, wealthier cities in developed regions. However, planning the layout of bicycle-sharing statio…
Hex2vec -- Context-Aware Embedding H3 Hexagons with OpenStreetMap Tags
Szymon Woźniak, Piotr Szymański
Representation learning of spatial and geographic data is a rapidly developing field which allows for similarity detection between areas and high-quality inference using deep neura…
Spatial Data Mining of Public Transport Incidents reported in Social Media
Kamil Raczycki, Marcin Szymański, Yahor Yeliseyenka +2
Public transport agencies use social media as an essential tool for communicating mobility incidents to passengers. However, while the short term, day-to-day information about tran…
WER we are and WER we think we are
Piotr Szymański, Piotr Żelasko, Mikolaj Morzy +6
Natural language processing of conversational speech requires the availability of high-quality transcripts. In this paper, we express our skepticism towards the recent reports of v…
Is the Best Better? Bayesian Statistical Model Comparison for Natural Language Processing
Piotr Szymański, Kyle Gorman
Recent work raises concerns about the use of standard splits to compare natural language processing models. We propose a Bayesian statistical model comparison technique which uses…