BERT
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Comedian Bert Kreischer says blood clot scare may have saved him from dying in a tour bus fire
Comedian Bert Kreischer revealed how suffering a terrifying medical ordeal may have saved his life. In early January, the 53-year-old "Free Bert" star went to the emergency room after severe leg pain woke him up in the middle of the night. At the hospital, doctors found a significant blood clot behind Kreischer's knee and then discovered additional clots in his lungs.
KliniskVestBERT: BERT Model Specialised to Norwegian Clinical Texts
arXiv:2606.01904v1 Announce Type: new Abstract: The increasing application of Natural Language Processing (NLP) in healthcare demands language models specifically attuned to the complexities of clinical language. This work introduces KliniskVestBERT, a suite of three BERT-based encoder models pre-trained on a substantial corpus of real-world, de-identified Norwegian clinical texts from Helse Vest. We continue pretraining existing language models Nb-BERT-large, NorBERT3-large, and ModernBERT...
KliniskVestBERT: BERT Model Specialised to Norwegian Clinical Texts
arXiv:2606.01904v2 Announce Type: replace Abstract: The increasing application of Natural Language Processing (NLP) in healthcare demands language models specifically attuned to the complexities of clinical language. This work introduces KliniskVestBERT, a suite of three BERT-based encoder models pre-trained on a substantial corpus of real-world, de-identified Norwegian clinical texts from Helse Vest. We continue pretraining existing language models Nb-BERT-large, NorBERT3-large, and...
Construction of Historical Knowledge Graphs Based on BERT and Graph Neural Networks
Announce Type: new Abstract: Through digital humanities research and scale-up historical data analysis, a significant amount of traditional historical text is converted into structured knowledge graphs. This paper provides a high-level architecture that combines bidirectional encoder representations of transformers (BERT) and graph neural networks (GNN) to extract the entities and relationships from various types of historical texts. The texts of traditional history resolve linguistic...
The Word and the Way: Strategies for Domain-Specific BERT Pre-Training in German Medical NLP
Announce Type: new Abstract: Digital healthcare generates vast amounts of clinical text that can support AI-assisted applications, yet German biomedical language models remain limited by older architectures or restricted training data. We present ChristBERT (Clinical- and Healthcare-Related Issues and Subjects Tuned BERT), a family of domain-specific German RoBERTa-based language models trained on a 13.5GB corpus of scientific publications, clinical texts, health-related web content, and...
Rare images capture pioneer life on WA's south coast in the early 1900s
Family gifts historical collection of images captured by pioneering WA photographer Bert Saw Sun 31 May 2026 at 10:06am The early days of settlement, young soldiers heading off to war and one of WA's first train lines being built are just some of the highly prized photos captured by one of Australia's earliest photographers. At the turn of the 20th century, Albany-born Bert Saw documented, in incredibly rare and beautiful detail, the life and experience of those living on the state's rugged...
GottBERT: a pure German Language Model
arXiv:2012.02110v2 Announce Type: replace Abstract: Pre-trained language models have significantly advanced natural language processing (NLP), especially with the introduction of BERT and its optimized version, RoBERTa. While initial research focused on English, single-language models can be advantageous compared to multilingual ones in terms of pre-training effort, overall resource efficiency or downstream task performance. Despite the growing popularity of prompt-based LLMs, more...
Interpreto: An Explainability Library for Transformers
arXiv:2512.09730v3 Announce Type: replace Abstract: Interpreto is an open-source Python library for interpreting HuggingFace language models, from early BERT variants to LLMs. It provides two complementary families of methods: attribution methods and concept-based explanations. The library bridges recent research and practical tooling by exposing explanation workflows through a unified API for both classification and text generation.
MimeLens: Position-Agnostic Content-Type Detection for Binary Fragments
arXiv:2606.04171v1 Announce Type: new Abstract: File-type classification underlies many workflows like malware triage, forensic carving, packet inspection, and storage indexing. Learned systems such as Google's Magika assume whole-file access at a known offset, so they break on the inputs many of these tasks actually produce, like a single packet payload, a header-less carved fragment, a random disk block, or a chunked upload. We introduce MimeLens, a family of small BERT-style encoders...
Predict and Reconstruct: Joint Objectives for Self-Supervised Language Representation Learning
arXiv:2606.05173v1 Announce Type: new Abstract: Masked language modelling (MLM) has been the dominant pre-training objective for text encoders since BERT, yet it encourages representations that are strongly anchored to surface-form token identity rather than deeper semantic structure. Inspired by the success of Joint Embedding Predictive Architectures (JEPA) (LeCun, 2022) in vision and audio, we propose a hybrid pre-training objective that combines a JEPA-style latent-space prediction loss...