https://github.com/jarfo/joint
공식 코드Joint Source-Target Self Attention with Locality Constraints
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Joint Source-Target Self Attention with Locality Constraints
Transform-Invariant Convolutional Neural Networks for Image Classification and Search
Learning Invariant Representations for Equivariant Neural Networks Using Orthogonal Moments
F-ViTA: Foundation Model Guided Visible to Thermal Translation
Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages
Modulating and attending the source image during encoding improves Multimodal Translation
Exploring Patch-wise Semantic Relation for Contrastive Learning in Image-to-Image Translation Tasks
Neural Machine Translation with Monolingual Translation Memory
Vega-MT: The JD Explore Academy Translation System for WMT22
On Adversarial Examples for Character-Level Neural Machine Translation
Towards Robust Event-based Networks for Nighttime via Unpaired Day-to-Night Event Translation
Broad-UNet: Multi-scale feature learning for nowcasting tasks
Pointer-based Fusion of Bilingual Lexicons into Neural Machine Translation
Adverse Weather Image Translation with Asymmetric and Uncertainty-aware GAN
Kreyòl-MT: Building MT for Latin American, Caribbean and Colonial African Creole Languages
Learning Kernel-Smoothed Machine Translation with Retrieved Examples
Learning and Analyzing Generation Order for Undirected Sequence Models
Vision Matters When It Should: Sanity Checking Multimodal Machine Translation Models
Towards Global AI Inclusivity: A Large-Scale Multilingual Terminology Dataset (GIST)
TVConv: Efficient Translation Variant Convolution for Layout-aware Visual Processing
A Simple Baseline to Semi-Supervised Domain Adaptation for Machine Translation
Improving Gloss-free Sign Language Translation by Reducing Representation Density
Exploiting Curriculum Learning in Unsupervised Neural Machine Translation
One Source, Two Targets: Challenges and Rewards of Dual Decoding
Integrating Translation Memories into Non-Autoregressive Machine Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.