https://github.com/theamrzaki/text_summurization_abstractive_methods
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/thomashuang2017/simpson-dialogue-gan-master
https://github.com/thomlake/pytorch-attention
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/thu-coai/ctrleval
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
https://github.com/thu-coai/ecm
https://github.com/thuiar/textoir-demo
https://github.com/thumt/THUMT
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/thunlp-mt/ckd
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/thunlp/TensorFlow-Summarization
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/timbmg/DIAL-LV
https://github.com/tongbao96/code-for-sfr-as
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
https://github.com/tree-park/kor-to-eng-translation
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/trusthlt/dp-rewrite
https://github.com/uber-research/PPLM
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
https://github.com/umeiko/mindspore-seq2seq
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/umutguneri/Question-Answering-Assistant
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/uzi0espil/research-papers-implementation/tree/master/Neural%20Machine%20Translation%20by%20Jointly%20Learning%20to%20Align%20and%20Translate
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/vGkatsis/Chat_Bot_DL
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/valerielimyh/Intent_Recognition_using_BERT
https://github.com/varun-bhaseen/Image-caption-generation-using-attention-model
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/varun-suresh/experiments-with-gpt2
https://github.com/venkat-ravilla/DAP
Guiding attention in Sequence-to-sequence models for Dialogue Act prediction
https://github.com/vikua/keras-attention-models
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/vincentcartillier/AVSD
https://github.com/voicy-ai/DialogStateTracking
https://github.com/vzhong/gazp
Grounded Adaptation for Zero-shot Executable Semantic Parsing
https://github.com/wangmz15/Chinese-Error-Correction-with-THUMT
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/wayalhruhi/julianser
Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation
https://github.com/wh0330/CAG_VisDial
https://github.com/whatissimondoing/his-dialog
Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context
https://github.com/whitepurple/Simple-NGram
https://github.com/wyu97/permgen
Text Generation from Knowledge Graphs with Graph Transformers
https://github.com/xcfcode/DHGN
https://github.com/xcfcode/Summarization-Papers
https://github.com/xcfcode/What-I-Have-Read
https://github.com/xhlulu/arxiv-assistant
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.