https://github.com/YvesWang/Machine_Translation_NLP
Neural Machine Translation by Jointly Learning to Align and Translate
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/ZephyrChenzf/SF-ID-Network-For-NLU
A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling
https://github.com/Zhihan1996/User-sim
https://github.com/ZurichNLP/sockeye
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/aaaceo890/Attention
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/aananda-giri/gpt2-nepali
https://github.com/aashutj/Multimodal-Multiparty-Emotion-Recognition-System-in-Conversation-Text-Mode-Only-
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
https://github.com/abhaskumarsinha/Corpus2GPT
https://github.com/abhaskumarsinha/MinimalGPT
https://github.com/abhaskumarsinha/Seq2Seq-Bahdanau-Attention-based-Encoder-Decoder-Language-Translator
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/abhishekr7/Summarization-of-Radiological-Reports
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/abhishekshakya/seq-2-seq-for-neural-machine-translation-english-to-hindi-
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/abmitra84/Machine_Translation
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/af1tang/personaGPT
Personalizing Dialogue Agents: I have a dog, do you have pets too?
https://github.com/affjljoo3581/GPT2
https://github.com/ai-agi/hicl
https://github.com/akanyaani/gpt-2-tensorflow2.0
https://github.com/akanyaani/minGPTF
https://github.com/alexa/alexa-with-dstc10-track2-dataset
"How Robust r u?": Evaluating Task-Oriented Dialogue Systems on Spoken Conversations
https://github.com/alibaba-damo-academy/FunASR
https://github.com/alibaba-damo-academy/funcodec
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT
https://github.com/alibabaresearch/damo-convai
Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing
https://github.com/amarazad/DSRNet
Meta-Context Transformers for Domain-Specific Response Generation
https://github.com/amazon-research/dstc11-track2-intent-induction
https://github.com/amazon-research/stil-mbart-multiatis
End-to-End Slot Alignment and Recognition for Cross-Lingual NLU
https://github.com/amazon-science/multiatis
End-to-End Slot Alignment and Recognition for Cross-Lingual NLU
https://github.com/amazon-science/tanl
Structured Prediction as Translation between Augmented Natural Languages
https://github.com/amolk/editsql
Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questions
https://github.com/ankurbhatia24/MULTIMODAL-EMOTION-RECOGNITION
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
https://github.com/aqzheng/Adversarial-Learning-for-Neural-Dialogue-Generation
https://github.com/arya46/VQA_HieCoAtt
Hierarchical Question-Image Co-Attention for Visual Question Answering
https://github.com/astorfi/neural-machine-translation-from-scratch
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/astorfi/sequence-to-sequence-from-scratch
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/atpaino/deep-text-corrector
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/aunabil4602/bnlp-workshop-task2-2023
https://github.com/avidale/arxivarius
Training Neural Response Selection for Task-Oriented Dialogue Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.