https://github.com/sambit9238/deep_text_corrector
Neural Machine Translation by Jointly Learning to Align and Translate
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Dialogue generation is the task of "understanding" natural language inputs - within natural language processing in order to produce output. The systems are usually intended for conversing with humans, for instance back and forth dialogue with a conversation agent like a chatbot. Some example benchmarks for this task (see others such as Natural Language Understanding) include FusedChat and Ubuntu DIalogue Corpus (UDC). Models can be evaluated via metrics such as BLEU, ROUGE, and METEOR albeit with challenges in terms of weak correlation with human judgement, that may be addressed by new ones like UnSupervised and Reference-free (USR) and Metric for automatic Unreferenced dialog evaluation (MaUde).
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Neural Machine Translation by Jointly Learning to Align and Translate
Personalizing Dialogue Agents: I have a dog, do you have pets too?
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
Explicit State Tracking with Semi-Supervision for Neural Dialogue Generation
Neural Machine Translation by Jointly Learning to Align and Translate
Stylized Dialogue Response Generation Using Stylized Unpaired Texts
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.