5 citations · 5 across the 9 of their papers we have counts for
9 papers
Schematize: An Agentic System for Generating and Refining Information-Extraction Schemas for Legal Research
Albert Sawczyn, Jakub Binkowski, Kamil Tagowski +3
Empirical legal research often relies on turning research questions into structured data extracted from large collections of rulings and judgments. Designing the extraction schema…
KG-Guard: Graph-Based Hallucination Detection for Knowledge Base Question Answering
Albert Sawczyn, Piotr Bielak, Tomasz Kajdanowicz
Large language models (LLMs) are increasingly used for knowledge base question answering (KBQA), where answering requires selecting entities from a question-specific knowledge-grap…
The Illusion of Progress: Re-evaluating Hallucination Detection in LLMs
Denis Janiak, Jakub Binkowski, Albert Sawczyn +3
Large language models (LLMs) have revolutionized natural language processing, yet their tendency to hallucinate poses serious challenges for reliable deployment. Despite numerous h…
FactSelfCheck: Fact-Level Black-Box Hallucination Detection for LLMs
Albert Sawczyn, Jakub Binkowski, Denis Janiak +2
Large Language Models (LLMs) frequently generate hallucinated content, posing significant challenges for applications where factuality is crucial. While existing hallucination dete…
Hallucination Detection in LLMs Using Spectral Features of Attention Maps
Jakub Binkowski, Denis Janiak, Albert Sawczyn +2
Large Language Models (LLMs) have demonstrated remarkable performance across various tasks but remain prone to hallucinations. Detecting hallucinations is essential for safety-crit…
Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction
Albert Sawczyn, Katsiaryna Viarenich, Konrad Wojtasik +4
Advancements in AI and natural language processing have revolutionized machine-human language interactions, with question answering (QA) systems playing a pivotal role. The knowled…
Empowering Small-Scale Knowledge Graphs: A Strategy of Leveraging General-Purpose Knowledge Graphs for Enriched Embeddings
Albert Sawczyn, Jakub Binkowski, Piotr Bielak +1
Knowledge-intensive tasks pose a significant challenge for Machine Learning (ML) techniques. Commonly adopted methods, such as Large Language Models (LLMs), often exhibit limitatio…
Graph-level representations using ensemble-based readout functions
Jakub Binkowski, Albert Sawczyn, Denis Janiak +2
Graph machine learning models have been successfully deployed in a variety of application areas. One of the most prominent types of models - Graph Neural Networks (GNNs) - provides…
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…