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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/lzccccc/SMOKE
공식 코드SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
https://github.com/m-3lab/fedmed-gan
공식 코드FedMed-GAN: Federated Domain Translation on Unsupervised Cross-Modality Brain Image Synthesis
https://github.com/m-resta/sg-rep
공식 코드Self-generated Replay Memories for Continual Neural Machine Translation
https://github.com/maats0519/maats_mqm
공식 코드MAATS: A Multi-Agent Automated Translation System Based on MQM Evaluation
https://github.com/machelreid/afromt
공식 코드AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages
https://github.com/machelreid/paradise
공식 코드PARADISE: Exploiting Parallel Data for Multilingual Sequence-to-Sequence Pretraining
https://github.com/machelreid/subformer
공식 코드Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers
https://github.com/machinelearning4health/medlane
공식 코드Benchmarking Automated Clinical Language Simplification: Dataset, Algorithm, and Evaluation
https://github.com/machinevision-seoultech/evci
공식 코드Image-to-Image Translation-based Data Augmentation for Robust EV Charging Inlet Detection
https://github.com/madaan/PML4DC-Comparable-Data-Collection
공식 코드Practical Comparable Data Collection for Low-Resource Languages via Images
https://github.com/madoibito80/im2sem
공식 코드Few-Shot Image-to-Semantics Translation for Policy Transfer in Reinforcement Learning
https://github.com/magarw/limit
공식 코드https://github.com/magiccircuit/treemix
공식 코드TreeMix: Compositional Constituency-based Data Augmentation for Natural Language Understanding
https://github.com/magnumresearchgroup/bash_gen
공식 코드NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
https://github.com/magnumresearchgroup/magnum-nlc2cmd
공식 코드NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
https://github.com/maharajbrahma/wat2024-multiindicmt
공식 코드NLIP_Lab-IITH Multilingual MT System for WAT24 MT Shared Task
https://github.com/mahfuzibnalam/terminology_evaluation
공식 코드On the Evaluation of Machine Translation for Terminology Consistency
https://github.com/mahfuzmohammad/brainomaly
공식 코드https://github.com/mahfuzmohammad/healthygan
공식 코드https://github.com/mainlp/SYGAR
공식 코드https://github.com/mainlp/crossre
공식 코드Multi-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction
https://github.com/mainlp/makieval
공식 코드https://github.com/majiangqin/Image-to-Recipe-Translation-using-AI
공식 코드https://github.com/makeshn/lobef_byte_nmt
공식 코드https://github.com/manandey/bias_machine_translation
공식 코드https://github.com/manestay/ecxtra
공식 코드https://github.com/mantra-inc/open-mantra-dataset
공식 코드https://github.com/manugar/imagestyletransfer
공식 코드https://github.com/manunarayanan/tulu-nmt
공식 코드https://github.com/mapto/UchitelnoEvangelie
공식 코드Computer-Aided Modelling of the Bilingual Word Indices to the Ninth-Century Uchitel'noe evangelie
https://github.com/marceloprates/Gender-Bias
공식 코드Assessing Gender Bias in Machine Translation -- A Case Study with Google Translate
https://github.com/marian-nmt/docmt23
공식 코드https://github.com/marian-nmt/marian
공식 코드https://github.com/marian-nmt/sotastream
공식 코드SOTASTREAM: A Streaming Approach to Machine Translation Training
https://github.com/marliesvanderwees/dds-nmt
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.