Type-Balanced Contextual Learning for Incremental Named Entity Recognition

arXiv:2608.31038 · cs.CL · Submitted 2026-08-31 · Read on arXiv

cs.CL

Submitted: 2026-08-31

Updated: 2026-08-31

Comments: Accepted by IEEE Transactions on Artificial Intelligence

Code: https://github.com/BladeDancer957/TBCL

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Catastrophic Forgetting — 21× in this paper · explained in 5 episodes
• Pseudo-labeling — 21× in this paper · explained in 3 episodes
• F1 Score — 19× in this paper · explained in 3 episodes
• Consistency — 18× in this paper · explained in 3 episodes
• Distillation — 10× in this paper · explained in 2 episodes
• Continual Learning — 7× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 6× in this paper
• Incremental Named Entity Recognition — 6× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• Type-Balanced Contextual Learning — 4× in this paper
• Benchmark — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Knowledge Distillation — 3× in this paper · explained in 11 episodes
• Objective Function — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Adaptability — 2× in this paper · explained in 1 episode
• Regularization — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Actor — 1× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• European Conference on Computer Vision — 1× in this paper
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• First Group — 1× in this paper
• Graph Construction — 1× in this paper · explained in 3 episodes
• International Conference on Machine Learning — 1× in this paper
• Loss Function — 1× in this paper · explained in 2 episodes
• Multimodal Learning — 1× in this paper · explained in 2 episodes
• Progressive Group — 1× in this paper
• Pruning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Transactions on Pattern Analysis and Machine Intelligence — 1× in this paper

Sources

• An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
• Distilling the Knowledge in a Neural Network
• HuggingFace's Transformers: State-of-the-art Natural Language Processing
• Incremental Learning with Maximum Entropy Regularization: Rethinking Forgetting and Intransigence
• RoBERTa: A Robustly Optimized BERT Pretraining Approach

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