3 papers
cs.CL2026
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…
cs.LG2025
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…
cs.CL2025
GLiNER-BioMed: A Suite of Efficient Models for Open Biomedical Named Entity Recognition
Anthony Yazdani, Ihor Stepanov, Douglas Teodoro
Biomedical named entity recognition (NER) presents unique challenges due to specialized vocabularies, the sheer volume of entities, and the continuous emergence of novel entities.…