https://github.com/2023-MindSpore-1/ms-code-219/tree/main/duconv
Multiple Generative Models Ensemble for Knowledge-Driven Proactive Human-Computer Dialogue Agent
Papers with Code 아카이브
Dialogue
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 21
- 평가표
- 1
- 보존된 평가 기록
- 1
Dialogue is notoriously hard to evaluate. Past approaches have used human evaluation.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/pangualpha
PanGu-Bot: Efficient Generative Dialogue Pre-training from Pre-trained Language Model
https://github.com/2023-MindSpore-4/Code6/tree/main/SDNet
SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering
https://github.com/A-Jacobson/minimal-nmt
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/ACE-VSIT/ACE-Ampethatic_bot
https://github.com/AIJoris/DPAC-DialogueGAN
https://github.com/AMNAALMGLY/NLP
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/AaronCCWong/Show-Attend-and-Tell
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/AjayKhalsa/convai_smile
Personalizing Dialogue Agents: I have a dog, do you have pets too?
https://github.com/Ambitioner-c/UserSimulator
https://github.com/AnuragBalsaraf/ERC
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
https://github.com/ArthurRizar/dialog_state_tracking_bert
Sequential Attention-based Network for Noetic End-to-End Response Selection
https://github.com/AtmaHou/UserSimulator
https://github.com/AuCson/SEDST
Explicit State Tracking with Semi-Supervision for Neural Dialogue Generation
https://github.com/BSlience/end2end-conversational-ai
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/Baichenjia/NMT-eager
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/CP8315-NNP-JLOPEZ/NNP-Chatbot
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/CatherineWong/dancin_seq2seq
https://github.com/Cenrax/Image-Captioning-with-Translation-
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/Cloud-CV/visual-chatbot
https://github.com/Cremiy/visdial-rl
Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning
https://github.com/DCYN/Ramdomized-Clinical-Trail-Classification
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/DevHyung/dialogue_cl
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/Digby-L/GNN-Conversation-Graph
https://github.com/Dipto084/Hierarchical-Fusion-for-Online-Multimodal-Dialog-Act-Classification
https://github.com/Epoch-Mengying/Generating-Poetry-with-Chatbot
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/ErikEkstedt/TurnGPT
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/EuphoriaYan/ChatRobot-For-Keras2
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/GaneshGS/data-and-models
https://github.com/Glaceon31/Document-Transformer
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/GuessWhatGame/guesswhat
End-to-end optimization of goal-driven and visually grounded dialogue systems
https://github.com/Guillem96/pointer-nn-pytorch
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/HemaDevaSagar35/NeuralMachineTranslation-French2English
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/IBM/dstc-noesis
https://github.com/IBM/dstc7-noesis
https://github.com/IS5882/Open-CyKG
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.