Papers
Research advancing document AI
Academic work behind our models for information extraction, document understanding and structured generation.
100+ citations across our published research
Publications
- 2024November 2024
NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data
Sergei Bogdanov, Alexandre Constantin, Timothée Bernard, Benoît Crabbé, Etienne BernardEMNLP 2024 — Conference on Empirical Methods in Natural Language ProcessingLarge Language Models have shown impressive abilities in data annotation, opening the way for new approaches to solve classic NLP problems. We show how to use LLMs to create NuNER, a compact language representation model specialized in Named Entity Recognition. NuNER can be fine-tuned to solve downstream NER problems in a data-efficient way, outperforming similarly-sized foundation models and competing with much larger LLMs.