Methods › Sequential › Bidirectional Recurrent Neural Networks › CNN BiLSTM

CNN Bidirectional LSTM

CNN BiLSTM

22 papers tagged archive 2025-07-28

Introduced by Jason P. C. Chiu et al. in Named Entity Recognition with Bidirectional LSTM-CNNs

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

A CNN BiLSTM is a hybrid bidirectional LSTM and CNN architecture. In the original formulation applied to named entity recognition, it learns both character-level and word-level features. The CNN component is used to induce the character-level features. For each word the model employs a convolution and a max pooling layer to extract a new feature vector from the per-character feature vectors such as character embeddings and (optionally) character type.

PaperSource

Papers archive 2025-07-28

22 shown of 22, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 62 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Named Entity Recognition (NER)6
Named Entity Recognition5
Sentence5
named-entity-recognition4
Representation Learning3
Data Augmentation2
Deep Learning2
Dependency Parsing2
Feature Engineering2
Word Embeddings2
Anatomy1
Attribute1
Automatic Sleep Stage Classification1
Binary Classification1
CAPTCHA Detection1
CCG Supertagging1
Clinical Assertion Status Detection1
Clinical Concept Extraction1
Contrastive Learning1
Decision Making1

Usage over time archive 2025-07-28

Papers per year tagged with CNN BiLSTM: 2015 to 2023, peak 7 7 0 2015: 1 paper 2015 2016: 0 papers 2016 2017: 0 papers 2017 2018: 1 paper 2018 2019: 4 papers 2019 2020: 7 papers 2020 2021: 4 papers 2021 2022: 2 papers 2022 2023: 3 papers 2023
Papers per year the archive tags with this method, by the paper's archive date (22 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Bidirectional Recurrent Neural Networks

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