https://github.com/pengshuang/Joint-Slot-Filling
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
Papers with Code 아카이브
Intent Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 4
- 보존된 평가 기록
- 10
Intent Classification is the task of correctly labeling a natural language utterance from a predetermined set of intents
Source: Multi-Layer Ensembling Techniques for Multilingual Intent Classification
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/phamnam-mta/ConveRT-PolyAI-Vietnamese
ConveRT: Efficient and Accurate Conversational Representations from Transformers
https://github.com/rparkin1/intent_LSTM
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
https://github.com/sogang-isds/TOATOD
Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System
https://github.com/sonos/svc-demographic-bias-assessment
https://github.com/sxjscience/GluonNLP-Slot-Filling
https://github.com/thuiar/textoir
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
https://github.com/thuiar/textoir-demo
An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction
https://github.com/wd929/NeMo
Efficient Sequence Transduction by Jointly Predicting Tokens and Durations
https://github.com/yinghao1019/Joint_learn
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
https://github.com/zhongyuchen/few-shot-text-classification
https://github.com/zhoucz97/JointBERT-paddle
https://gitlab.com/Jaco-Assistant/Jaco-Master
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.