https://github.com/andrewilyas/ens-adv-train-attack
Towards Deep Learning Models Resistant to Adversarial Attacks
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Part-of-speech tagging (POS tagging) is the task of tagging a word in a text with its part of speech. A part of speech is a category of words with similar grammatical properties. Common English parts of speech are noun, verb, adjective, adverb, pronoun, preposition, conjunction, etc.
Example:
| Vinken | , | 61 | years | old |
|---|---|---|---|---|
| NNP | , | CD | NNS | JJ |
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Towards Deep Learning Models Resistant to Adversarial Attacks
Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Recurrent Neural Network
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
Towards Deep Learning Models Resistant to Adversarial Attacks
A Robust Transformation-Based Learning Approach Using Ripple Down Rules for Part-of-Speech Tagging
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Recurrent Neural Network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.