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TENER: Adapting Transformer Encoder for Named Entity Recognition

arXiv 1911.04474 ↗First posted 10 Nov 2019cs.CL cs.LGcited by 69

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Abstract (arXiv)

The Bidirectional long short-term memory networks (BiLSTM) have been widely used as an encoder in models solving the named entity recognition (NER) task. Recently, the Transformer is broadly adopted in various Natural Language Processing (NLP) tasks owing to its parallelism and advantageous performance. Nevertheless, the performance of the Transformer in NER is not as good as it is in other NLP tasks. In this paper, we propose TENER, a NER architecture adopting adapted Transformer Encoder to model the character-level features and word-level features. By incorporating the direction and relative distance aware attention and the un-scaled attention, we prove the Transformer-like encoder is just as effective for NER as other NLP tasks.

Key facts. Cited by 69 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Nov 2019.

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Citing papers per year: 2021: 20; 2022: 23; 2023: 17; 2024: 5; 2025: 4.

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  1. 2021A Survey of Transformerscited by 399
  2. 2021A Unified Generative Framework for Various NER Subtaskscited by 141
  3. 2022MetaFormer Baselines for Visioncited by 131
  4. 2021Position Information in Transformers: An Overviewcited by 103
  5. 2021Mixed Transformer U-Net For Medical Image Segmentationcited by 95
  6. 2021Unified Named Entity Recognition as Word-Word Relation Classificationcited by 89
  7. 2024A Temporal Kolmogorov-Arnold Transformer for Time Series Forecastingcited by 50
  8. 2021A Partition Filter Network for Joint Entity and Relation Extractioncited by 42
  9. 2022Dissecting Transformer Length Extrapolation via the Lens of Receptive Field Analysiscited by 39
  10. 2021Accelerating BERT Inference for Sequence Labeling via Early-Exitcited by 29
  11. 2023Pushing the Limits of ChatGPT on NLP Taskscited by 27
  12. 2023NBIAS: A Natural Language Processing Framework for Bias Identification in Textcited by 23
38 more
  1. 2024When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challengescited by 20
  2. 2022MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspectivecited by 17
  3. 2021Simplified DOM Trees for Transferable Attribute Extraction from the Webcited by 16
  4. 2022TransLIST: A Transformer-Based Linguistically Informed Sanskrit Tokenizercited by 13
  5. 2022Understanding the Failure of Batch Normalization for Transformers in NLPcited by 12
  6. 2021PiSLTRc: Position-informed Sign Language Transformer with Content-aware Convolutioncited by 11
  7. 2021TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Datacited by 10
  8. 2022Token-level Sequence Labeling for Spoken Language Understanding using Compositional End-to-End Modelscited by 10
  9. 2022PUnifiedNER: A Prompting-based Unified NER System for Diverse Datasetscited by 10
  10. 2021End-to-End Dense Video Grounding via Parallel Regressioncited by 9
  11. 2022O-ViT: Orthogonal Vision Transformercited by 9
  12. 2021Less is More: Pre-train a Strong Text Encoder for Dense Retrieval Using a Weak Decodercited by 7
  13. 2021Multi-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognitioncited by 7
  14. 2022An Embarrassingly Easy but Strong Baseline for Nested Named Entity Recognitioncited by 7
  15. 2023MAWSEO: Adversarial Wiki Search Poisoning for Illicit Online Promotioncited by 7
  16. 2023E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognitioncited by 7
  17. 2021Speech2Slot: An End-to-End Knowledge-based Slot Filling from Speechcited by 6
  18. 2025Hallucinated Span Detection with Multi-View Attention Featurescited by 6
  19. 2025Deep Probabilistic Modeling of User Behavior for Anomaly Detection via Mixture Density Networkscited by 6
  20. 2023DiffusionNER: Boundary Diffusion for Named Entity Recognitioncited by 5
  21. 2023Co-Speech Gesture Detection through Multi-Phase Sequence Labelingcited by 5
  22. 2021Larger-Context Tagging: When and Why Does It Work?cited by 4
  23. 2021DyLex: Incorporating Dynamic Lexicons into BERT for Sequence Labelingcited by 4
  24. 2022TURNER: The Uncertainty-based Retrieval Framework for Chinese NERcited by 4
  25. 2022Searching a High-Performance Feature Extractor for Text Recognition Networkcited by 4
  26. 2023PromptNER: A Prompting Method for Few-shot Named Entity Recognition via k Nearest Neighbor Searchcited by 4
  27. 2023Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspectivecited by 4
  28. 2023Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Settingcited by 4
  29. 2023Integrating Chemical Language and Molecular Graph in Multimodal Fused Deep Learning for Drug Property Predictioncited by 4
  30. 2022Exploring the Value of Pre-trained Language Models for Clinical Named Entity Recognitioncited by 3
  31. 2023A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognitioncited by 3
  32. 2024Mitigating Out-of-Entity Errors in Named Entity Recognition: A Sentence-Level Strategycited by 3
  33. 2021De-identifying Australian Hospital Discharge Summaries: An End-to-End Framework using Ensemble of Deep Learning Modelscited by 2
  34. 2022NERDA-Con: Extending NER models for Continual Learning -- Integrating Distinct Tasks and Updating Distribution Shiftscited by 2
  35. 2022Win-Win Cooperation: Bundling Sequence and Span Models for Named Entity Recognitioncited by 2
  36. 2022Unsupervised Boundary-Aware Language Model Pretraining for Chinese Sequence Labelingcited by 2
  37. 2023BLSTM-Based Confidence Estimation for End-to-End Speech Recognitioncited by 2
  38. 2024CRepair: CVAE-based Automatic Vulnerability Repair Technologycited by 2

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