Cover Image

Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Golde, Jonas, Haller, Patrick, Ploner, Max, Barth, Fabio, Jedema, Nicolaas, Akbik, Alan
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FiNERweb: Datasets and Artifacts for Scalable Multilingual Named Entity Recognition
by: Golde, Jonas, et al.
Published: (2025)

What Matters When Building Universal Multilingual Named Entity Recognition Models?
by: Golde, Jonas, et al.
Published: (2026)

Large-Scale Label Interpretation Learning for Few-Shot Named Entity Recognition
by: Golde, Jonas, et al.
Published: (2024)

MastermindEval: A Simple But Scalable Reasoning Benchmark
by: Golde, Jonas, et al.
Published: (2025)

BabyHGRN: Exploring RNNs for Sample-Efficient Training of Language Models
by: Haller, Patrick, et al.
Published: (2024)

PISA-Bench: The PISA Index as a Multilingual and Multimodal Metric for the Evaluation of Vision-Language Models
by: Haller, Patrick, et al.
Published: (2025)

Sample-Efficient Language Modeling with Linear Attention and Lightweight Enhancements
by: Haller, Patrick, et al.
Published: (2025)

PECC: Problem Extraction and Coding Challenges
by: Haller, Patrick, et al.
Published: (2024)

What Matters in Linearizing Language Models? A Comparative Study of Architecture, Scale, and Task Adaptation
by: Haller, Patrick, et al.
Published: (2025)

Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
by: Golde, Jonas, et al.
Published: (2023)

From Data to Knowledge: Evaluating How Efficiently Language Models Learn Facts
by: Christoph, Daniel, et al.
Published: (2025)

LM-PUB-QUIZ: A Comprehensive Framework for Zero-Shot Evaluation of Relational Knowledge in Language Models
by: Ploner, Max, et al.
Published: (2024)

Hierarchical Text Classification with LLM-Refined Taxonomies
by: Golde, Jonas, et al.
Published: (2026)

Towards a Principled Evaluation of Knowledge Editors
by: Pohl, Sebastian, et al.
Published: (2025)

BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models
by: Wiland, Jacek, et al.
Published: (2024)

NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition
by: Merdjanovska, Elena, et al.
Published: (2024)

TransformerRanker: A Tool for Efficiently Finding the Best-Suited Language Models for Downstream Classification Tasks
by: Garbas, Lukas, et al.
Published: (2024)

Question Decomposition for Retrieval-Augmented Generation
by: Ammann, Paul J. L., et al.
Published: (2025)

Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling
by: Aynetdinov, Ansar, et al.
Published: (2026)

Evaluating Design Decisions for Dual Encoder-based Entity Disambiguation
by: Rücker, Susanna, et al.
Published: (2025)

Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework
by: Averly, Reza, et al.
Published: (2024)

A Cooperative Multi-Agent Framework for Zero-Shot Named Entity Recognition
by: Wang, Zihan, et al.
Published: (2025)

SAM-NER: Semantic Archetype Mediation for Zero-Shot Named Entity Recognition
by: Cai, Ruichu, et al.
Published: (2026)

Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models
by: Xie, Tingyu, et al.
Published: (2023)

LLMs are Better Than You Think: Label-Guided In-Context Learning for Named Entity Recognition
by: Bai, Fan, et al.
Published: (2025)

A Unified Label-Aware Contrastive Learning Framework for Few-Shot Named Entity Recognition
by: Zhang, Haojie, et al.
Published: (2024)

Nested Named Entity Recognition as Single-Pass Sequence Labeling
by: Muñoz-Ortiz, Alberto, et al.
Published: (2025)

Large Language Models for Few-Shot Named Entity Recognition
by: Zhao, Yufei, et al.
Published: (2018)

In-Context Learning for Few-Shot Nested Named Entity Recognition
by: Zhang, Meishan, et al.
Published: (2024)

Evaluating Named Entity Recognition Using Few-Shot Prompting with Large Language Models
by: Zeghidi, Hédi, et al.
Published: (2024)

Meta-Pretraining for Zero-Shot Cross-Lingual Named Entity Recognition in Low-Resource Philippine Languages
by: Africa, David Demitri, et al.
Published: (2025)

OEMA: Ontology-Enhanced Multi-Agent Collaboration Framework for Zero-Shot Clinical Named Entity Recognition
by: Tao, Xinli, et al.
Published: (2025)

Zero- and Few-Shot Named-Entity Recognition: Case Study and Dataset in the Crime Domain (CrimeNER)
by: Lopez-Duran, Miguel, et al.
Published: (2026)

llmNER: (Zero|Few)-Shot Named Entity Recognition, Exploiting the Power of Large Language Models
by: Villena, Fabián, et al.
Published: (2024)

DynClean: Training Dynamics-based Label Cleaning for Distantly-Supervised Named Entity Recognition
by: Zhang, Qi, et al.
Published: (2025)

Pre-Training Curriculum for Multi-Token Prediction in Language Models
by: Aynetdinov, Ansar, et al.
Published: (2025)

Prompt Tuning for Few-Shot Continual Learning Named Entity Recognition
by: Ren, Zhe
Published: (2025)

BANER: Boundary-Aware LLMs for Few-Shot Named Entity Recognition
by: Guo, Quanjiang, et al.
Published: (2024)

Local LLM Ensembles for Zero-shot Portuguese Named Entity Recognition
by: Sarcinelli, João Lucas Luz Lima, et al.
Published: (2025)

Named Entity Recognition in Context
by: Brisson, Colin, et al.
Published: (2025)