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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 5
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zouharvi/mt-metric-estimation
공식 코드Poor Man's Quality Estimation: Predicting Reference-Based MT Metrics Without the Reference
https://github.com/zouharvi/ptakopet
공식 코드https://github.com/zouharvi/reference-mt-distill
공식 코드Sampling and Filtering of Neural Machine Translation Distillation Data
https://github.com/zouharvi/vocab-stealing
공식 코드Stolen Subwords: Importance of Vocabularies for Machine Translation Model Stealing
https://github.com/zsyzzsoft/co-mod-gan
공식 코드Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
https://github.com/zurichnlp/contradecode
공식 코드https://github.com/zurichnlp/coverage-contrastive-conditioning
공식 코드https://github.com/zurichnlp/mbr-sensitivity
공식 코드https://github.com/zurichnlp/multipivotnmt
공식 코드Investigating Multi-Pivot Ensembling with Massively Multilingual Machine Translation Models
https://github.com/zurichnlp/nmtscore
공식 코드NMTScore: A Multilingual Analysis of Translation-based Text Similarity Measures
https://github.com/zurichnlp/segtest
공식 코드How Suitable Are Subword Segmentation Strategies for Translating Non-Concatenative Morphology?
https://github.com/zurichnlp/spoken-to-signed-translation
공식 코드An Open-Source Gloss-Based Baseline for Spoken to Signed Language Translation
https://github.com/zurichnlp/translation-direction-detection
공식 코드Machine Translation Models are Zero-Shot Detectors of Translation Direction
https://github.com/zurichnlp/window_audio_segmentation
공식 코드Don't Discard Fixed-Window Audio Segmentation in Speech-to-Text Translation
https://github.com/zwhe99/MAPS-mt
공식 코드Exploring Human-Like Translation Strategy with Large Language Models
https://github.com/zwhe99/feedbackmt
공식 코드https://github.com/zwhe99/selftraining4unmt
공식 코드Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation
https://github.com/zwhe99/wmt22-en-liv
공식 코드https://github.com/zzsfornlp/znmt-merge
공식 코드Exploring Recombination for Efficient Decoding of Neural Machine Translation
https://gitlab.com/abhe/syntheticpet-trpms22
공식 코드https://gitlab.com/bsmetsjr/lietorch
공식 코드https://gitlab.com/cian.unibas.ch/diffusion-anomaly
공식 코드https://gitlab.com/codegenfact/BertranX
공식 코드The impact of lexical and grammatical processing on generating code from natural language
https://gitlab.com/codegenfactors/BertranX
공식 코드The impact of lexical and grammatical processing on generating code from natural language
https://gitlab.com/farid-fari/fewshot-learning
공식 코드https://gitlab.com/jarmill/Ribosomes
공식 코드https://gitlab.com/nct_tso_public/constructs
공식 코드https://gitlab.com/nct_tso_public/laparoscopic-image-2-image-translation
공식 코드https://gitlab.com/nct_tso_public/surgical-video-sim2real
공식 코드Long-Term Temporally Consistent Unpaired Video Translation from Simulated Surgical 3D Data
https://gitlab.com/openpixi/scalar_ml
공식 코드Generalization capabilities of translationally equivariant neural networks
https://gitlab.com/skalo/baroque-nmt
공식 코드Modeling Baroque Two-Part Counterpoint with Neural Machine Translation
https://gitlab.com/verenich/gcmlpub
공식 코드https://huggingface.co/datasets/MLCommons/speech-wikimedia
공식 코드https://huggingface.co/disk0dancer/ruBert-base-finetuned-pos
공식 코드POS-tagging to highlight the skeletal structure of sentences
https://huggingface.co/naist-nlp/mitre_466m
공식 코드Registering Source Tokens to Target Language Spaces in Multilingual Neural Machine Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.