5 citations · 6 across the 8 of their papers we have counts for
8 papers
A Geometry-Based View of Mahalanobis OOD Detection
Denis Janiak, Jakub Binkowski, Tomasz Kajdanowicz
Out-of-distribution (OOD) detection is critical for reliable deployment of vision models. Mahalanobis-based detectors remain strong baselines, yet their performance varies widely a…
Rethinking the Evaluation of Alignment Methods: Insights into Diversity, Generalisation, and Safety
Denis Janiak, Julia Moska, Dawid Motyka +4
Large language models (LLMs) require careful alignment to balance competing objectives - factuality, safety, conciseness, proactivity, and diversity. Existing studies focus on indi…
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…
Unveiling the Potential of Probabilistic Embeddings in Self-Supervised Learning
Denis Janiak, Jakub Binkowski, Piotr Bielak +1
In recent years, self-supervised learning has played a pivotal role in advancing machine learning by allowing models to acquire meaningful representations from unlabeled data. An i…
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…