https://github.com/fallcat/stupidNMT
공식 코드Hard-Coded Gaussian Attention for Neural Machine Translation
Papers with Code 아카이브
Translation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/fandongmeng/DTMT_InDec
공식 코드DTMT: A Novel Deep Transition Architecture for Neural Machine Translation
https://github.com/fanny-jourdan/FairTranslate
공식 코드https://github.com/fantabulous-j/class
공식 코드Pre-training Cross-lingual Open Domain Question Answering with Large-scale Synthetic Supervision
https://github.com/faridghm/meta-sel
공식 코드3D-model ShapeNet Core Classification using Meta-Semantic Learning
https://github.com/fartashf/vsepp
공식 코드Target-Oriented Deformation of Visual-Semantic Embedding Space
https://github.com/fatemeh-azadi/unsupervised-qe
공식 코드Mismatching-Aware Unsupervised Translation Quality Estimation For Low-Resource Languages
https://github.com/fe1ixxu/BiBERT
공식 코드BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation
https://github.com/fe1ixxu/ZeroShot-CrossLing-Parsing
공식 코드Zero-Shot Cross-Lingual Dependency Parsing through Contextual Embedding Transformation
https://github.com/fe1ixxu/alma
공식 코드A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models
https://github.com/fe1ixxu/cd_id_mmt
공식 코드Language-Aware Multilingual Machine Translation with Self-Supervised Learning
https://github.com/fe1ixxu/intra-distillation
공식 코드The Importance of Being Parameters: An Intra-Distillation Method for Serious Gains
https://github.com/fe1ixxu/lms_fd
공식 코드Condensing Multilingual Knowledge with Lightweight Language-Specific Modules
https://github.com/fe1ixxu/stratified_mixture_of_experts
공식 코드Towards Being Parameter-Efficient: A Stratified Sparsely Activated Transformer with Dynamic Capacity
https://github.com/fei-hdu/sRender
공식 코드Bridging Unpaired Facial Photos And Sketches By Line-drawings
https://github.com/feiwang3311/Lantern
공식 코드Demystifying Differentiable Programming: Shift/Reset the Penultimate Backpropagator
https://github.com/fengpeng-yue/speech-to-speech-translation
공식 코드Leveraging Pseudo-labeled Data to Improve Direct Speech-to-Speech Translation
https://github.com/ferg-lab/pines
공식 코드https://github.com/fidansamet/ganiry
공식 코드https://github.com/flair-iisc/watermark_tradeoffs
공식 코드https://github.com/flc777/glat
공식 코드Glancing Transformer for Non-Autoregressive Neural Machine Translation
https://github.com/flegyas/latent-translation
공식 코드https://github.com/fnzhan/AMT
공식 코드Bi-level Feature Alignment for Versatile Image Translation and Manipulation
https://github.com/fnzhan/RABIT
공식 코드Bi-level Feature Alignment for Versatile Image Translation and Manipulation
https://github.com/for-ai/m-rewardbench
공식 코드M-RewardBench: Evaluating Reward Models in Multilingual Settings
https://github.com/formiel/fairseq
공식 코드Lightweight Adapter Tuning for Multilingual Speech Translation
https://github.com/formiel/fairseq/blob/master/examples/speech_to_text/docs/adapters.md
공식 코드Lightweight Adapter Tuning for Multilingual Speech Translation
https://github.com/formiel/speech-translation
공식 코드Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech Translation
https://github.com/franckbrl/nmt-pseudo-source-discriminator
공식 코드Using Monolingual Data in Neural Machine Translation: a Systematic Study
https://github.com/francois-meyer/ssmt
공식 코드Subword Segmental Machine Translation: Unifying Segmentation and Target Sentence Generation
https://github.com/frankkramer-lab/GERNERMED
공식 코드https://github.com/frednam93/FDY-SED
공식 코드Frequency Dynamic Convolution: Frequency-Adaptive Pattern Recognition for Sound Event Detection
https://github.com/freesunshine0316/semantic-nmt
공식 코드https://github.com/freewym/espresso
공식 코드Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
https://github.com/frozentoad9/CMST
공식 코드Prabhupadavani: A Code-mixed Speech Translation Data for 25 Languages
https://github.com/frxxzhl/ssebt
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.