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20242026
most citedGLiNER multi-task: Generalist Lightweight Model for Various Information Extraction Tasks

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2026

SCX Router: Streaming Zero-Shot Model Selection with a Decoder-KV Classifier and a Real-World Task Ontology

Ihor Stepanov, Aleksandr Smechov, Mykhailo Shtopko +2

The rapid proliferation of large language models (LLMs) and the growing diversity of their applications presents a unique optimization opportunity: selecting the right model for th…

cs.CL2026

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…

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.LG20243 cited

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…