NE-R1: Enhancing Named Entity Recognition Model via Reinforcement Learning

arXiv:2609.02366 · cs.CL, cs.AI · Submitted 2026-09-02 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-02

Updated: 2026-09-02

Terminology

• Named Entity Recognition — 25× in this paper
• Actor — 23× in this paper · explained in 3 episodes
• RAG — 19× in this paper · explained in 3 episodes
• Benchmark — 17× in this paper · explained in 2 episodes
• GRPO — 9× in this paper · explained in 6 episodes
• Instruction Tuning — 9× in this paper · explained in 2 episodes
• F1 Score — 8× in this paper · explained in 3 episodes
• Reinforcement Learning — 8× in this paper · explained in 4 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Ablation — 6× in this paper · explained in 1 episode
• Multi-Task Capability Initialization — 6× in this paper
• Natural Language Processing — 6× in this paper
• Group Relative Policy Optimization — 3× in this paper
• Two-stage training — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Group Relative Policy Optimization (GRPO) — 2× in this paper · explained in 5 episodes
• Hallucination — 2× in this paper · explained in 3 episodes
• Named Entity Recognition (NER) — 2× in this paper · explained in 2 episodes
• Text-to-SQL — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Active Learning — 1× in this paper · explained in 6 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• GRPO Objective — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Perplexity — 1× in this paper · explained in 3 episodes
• Pseudo-labels — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Zero-Shot Transfer — 1× in this paper · explained in 4 episodes

Sources

• PromptNER: Prompting For Named Entity Recognition
• Improving Pseudo Labels with Global-Local Denoising Framework for Cross-lingual Named Entity Recognition
• MT-R1-Zero: Advancing LLM-based Machine Translation via R1-Zero-like Reinforcement Learning
• Retrieval-Augmented Generation for Large Language Models: A Survey
• Proximal Policy Optimization Algorithms
• R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement Learning
• Corrective Retrieval Augmented Generation

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