https://github.com/deepsense-ai/unblackboxing_webinar
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/devJWSong/bert-crf-entity-recognition-pytorch
ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation
https://github.com/devJWSong/gpt2-chatbot-pytorch
Personalizing Dialogue Agents: I have a dog, do you have pets too?
https://github.com/devjwsong/gpt2-dialogue-generation-pytorch
Personalizing Dialogue Agents: I have a dog, do you have pets too?
https://github.com/devjwsong/t5-dst-modified-pytorch
https://github.com/digitalphonetics/speaker-anonymization
https://github.com/dinobby/hypemo
Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset
https://github.com/dirtdust/TC-Bot-python3
https://github.com/distractor-generation/dg_survey
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/dladustn95/ENMODEL
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/dladustn95/dialogGenerator_transformer
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/dladustn95/enLanguageModel
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/dmitriy-serdyuk/arxiv2kindle
https://github.com/dmlc/dgl/tree/master/examples/pytorch/graphwriter
Text Generation from Knowledge Graphs with Graph Transformers
https://github.com/dongdong199408/teachchatrobot
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/dreasysnail/CoCon
Consistent Dialogue Generation with Self-supervised Feature Learning
https://github.com/dscripka/openwakeword
Speech Model Pre-training for End-to-End Spoken Language Understanding
https://github.com/durashi/Dialog_policy_network_for_low_resource_setting
https://github.com/dvlab-research/MGM
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
https://github.com/egillian1/AblationPLATO
PLATO: Pre-trained Dialogue Generation Model with Discrete Latent Variable
https://github.com/eric-mitchell/serac
https://github.com/eske/seq2seq
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/evelynyou/w266_project
Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset
https://github.com/facebookresearch/ParlAI/tree/master/projects/wizard_of_wikipedia
Wizard of Wikipedia: Knowledge-Powered Conversational agents
https://github.com/facebookresearch/accentor
https://github.com/facebookresearch/corefnmn
Visual Coreference Resolution in Visual Dialog using Neural Module Networks
https://github.com/farizrahman4u/seq2seq
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/fighting41love/funNLP
CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset
https://github.com/frozentoad9/Neural-Machine-Translation
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/garygsw/Nav-NNDial
https://github.com/gicheonkang/prograsp
The Dialog Must Go On: Improving Visual Dialog via Generative Self-Training
https://github.com/glamor-usc/teach_tatc
https://github.com/glicerico/SGNN
https://github.com/gmftbyGMFTBY/HashRetrieval
Group-wise Contrastive Learning for Neural Dialogue Generation
https://github.com/gongrennengzhi/nmt
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/gongshuangshuang/deep-text-corrector
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.