https://github.com/XiudingCai/EnCo-pytorch
공식 코드Rethinking the Paradigm of Content Constraints in Unpaired Image-to-Image Translation
Papers with Code 아카이브
Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/XuezheMax/fairseq-apollo
공식 코드https://github.com/XuezheMax/flowseq
공식 코드FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow
https://github.com/Yan98/S2FGAN
공식 코드S2FGAN: Semantically Aware Interactive Sketch-to-Face Translation
https://github.com/YangNaruto/FQ-GAN
공식 코드https://github.com/YangNaruto/latent-energy-transport
공식 코드Unpaired Image-to-Image Translation via Latent Energy Transport
https://github.com/YannDubs/Neural-Process-Family
공식 코드Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
https://github.com/Yonsei-STL/pix2next
공식 코드Pix2Next: Leveraging Vision Foundation Models for RGB to NIR Image Translation
https://github.com/Yorko/gender-unbiased_BERT-based_pronoun_resolution
공식 코드https://github.com/YuanXue1993/WireframeRenderer
공식 코드Neural Wireframe Renderer: Learning Wireframe to Image Translations
https://github.com/YueLiu/NeuralTripleTranslation
공식 코드Seq2RDF: An end-to-end application for deriving Triples from Natural Language Text
https://github.com/YukeWang96/TCGNN-Pytorch
공식 코드TC-GNN: Bridging Sparse GNN Computation and Dense Tensor Cores on GPUs
https://github.com/YumingZHAI/ctp
공식 코드Towards Recognizing Phrase Translation Processes: Experiments on English-French
https://github.com/YunChunChen/NAS-DIP-pytorch
공식 코드NAS-DIP: Learning Deep Image Prior with Neural Architecture Search
https://github.com/Yusser96/Exploring-Paracrawl-for-Document-level-Neural-Machine-Translation
공식 코드Exploring Paracrawl for Document-level Neural Machine Translation
https://github.com/YuweiYin/CROP
공식 코드https://github.com/YuweiYin/GTrans
공식 코드GTrans: Grouping and Fusing Transformer Layers for Neural Machine Translation
https://github.com/YuweiYin/HLT-MT
공식 코드HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine Translation
https://github.com/YuweiYin/UM4
공식 코드https://github.com/ZNLP/SOTA-MT
공식 코드https://github.com/ZNLP/sb-nmt
공식 코드Synchronous Bidirectional Inference for Neural Sequence Generation
https://github.com/ZhangShiyue/ChrEn
공식 코드ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
https://github.com/ZhangShiyue/ChrEnTranslate
공식 코드https://github.com/ZhenYangIACAS/NMT_GAN
공식 코드Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets
https://github.com/ZhenYangIACAS/unsupervised-NMT
공식 코드https://github.com/ZhengZerong/DeepHuman
공식 코드https://github.com/Zhenzi-Weng/LaSC-ST
공식 코드Large Model Empowered Streaming Speech Semantic Communications
https://github.com/ZikangZhou/QCNet
공식 코드QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction
https://github.com/ZurichNLP/ContraPro
공식 코드https://github.com/ZurichNLP/domain-robustness
공식 코드https://github.com/ZurichNLP/mt-parity-assessment-data
공식 코드A Set of Recommendations for Assessing Human-Machine Parity in Language Translation
https://github.com/ZurichNLP/multiturn-llm-docmt
공식 코드Source-primed Multi-turn Conversation Helps Large Language Models Translate Documents
https://github.com/ZurichNLP/sockeye
공식 코드https://github.com/ZurichNLP/understanding-mbr
공식 코드Understanding the Properties of Minimum Bayes Risk Decoding in Neural Machine Translation
https://github.com/a514514772/DISE-Domain-Invariant-Structure-Extraction
공식 코드https://github.com/aair-lab/auto-llm-assessment
공식 코드$\forall$uto$\exists$val: Autonomous Assessment of LLMs in Formal Synthesis and Interpretation Tasks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.