4 papers
GLiNER-Relex: A Unified Framework for Joint Named Entity Recognition and Relation Extraction
Ihor Stepanov, Oleksandr Lukashov, Mykhailo Shtopko +1
Joint named entity recognition (NER) and relation extraction (RE) is a fundamental task in natural language processing for constructing knowledge graphs from unstructured text. Whi…
The Million-Label NER: Breaking Scale Barriers with GLiNER bi-encoder
Ihor Stepanov, Mykhailo Shtopko, Dmytro Vodianytskyi +1
This paper introduces GLiNER-bi-Encoder, a novel architecture for Named Entity Recognition (NER) that harmonizes zero-shot flexibility with industrial-scale efficiency. While the o…
GLiClass: Generalist Lightweight Model for Sequence Classification Tasks
Ihor Stepanov, Mykhailo Shtopko, Dmytro Vodianytskyi +3
Classification is one of the most widespread tasks in AI applications, serving often as the first step in filtering, sorting, and categorizing data. Since modern AI systems must ha…
GLiNER multi-task: Generalist Lightweight Model for Various Information Extraction Tasks
Ihor Stepanov, Mykhailo Shtopko
Information extraction tasks require both accurate, efficient, and generalisable models. Classical supervised deep learning approaches can achieve the required performance, but the…