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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nkdinsdale/challenges_review
공식 코드Challenges for machine learning in clinical translation of big data imaging studies
https://github.com/nlp-dke/NMTGMinor/tree/master/recipes/zero-shot
공식 코드Improving Zero-Shot Translation by Disentangling Positional Information
https://github.com/nlp2ct/consisttl
공식 코드ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation
https://github.com/nlp2ct/e-att
공식 코드https://github.com/nlp2ct/hil-mt
공식 코드Human-in-the-loop Machine Translation with Large Language Model
https://github.com/nlp2ct/unite
공식 코드https://github.com/nlp2ct/variance-aware-mt-test-sets
공식 코드https://github.com/nlpcuom/quality-matters
공식 코드Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora
https://github.com/noabrazilay/missgan
공식 코드https://github.com/noe/sparsely_factored_nmt
공식 코드https://github.com/noegroup/EDMnets
공식 코드https://github.com/nolongerprejudice/tgbi
공식 코드On Measuring Gender Bias in Translation of Gender-neutral Pronouns
https://github.com/nttcslab-nlp/doc_lm
공식 코드https://github.com/nttcslab-nlp/simplifyingmt_acl24
공식 코드https://github.com/ntunlp/pronoun-finetuning
공식 코드https://github.com/numerical-geometric-algebra/registrationga
공식 코드Correspondence Free Multivector Cloud Registration using Conformal Geometric Algebra
https://github.com/nunpuking/end-to-end-backtranslation
공식 코드End-to-End Training for Back-Translation with Categorical Reparameterization Trick
https://github.com/nusnlp/c2e-mt-benchmark
공식 코드Upping the Ante: Towards a Better Benchmark for Chinese-to-English Machine Translation
https://github.com/nusnlp/mlconvgec2018
공식 코드A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction
https://github.com/nvlabs/MUNIT
공식 코드https://github.com/nvlabs/imaginaire
공식 코드COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder
https://github.com/nvog/lost-in-interpretation
공식 코드Lost in Interpretation: Predicting Untranslated Terminology in Simultaneous Interpretation
https://github.com/nxphi47/data_diversification
공식 코드Data Diversification: A Simple Strategy For Neural Machine Translation
https://github.com/nxphi47/multiagent_crosstranslate
공식 코드Cross-model Back-translated Distillation for Unsupervised Machine Translation
https://github.com/nxphi47/refine_unsup_multilingual_mt
공식 코드Refining Low-Resource Unsupervised Translation by Language Disentanglement of Multilingual Model
https://github.com/nyu-dl/NLP_DL_Lecture_Note
공식 코드Natural Language Understanding with Distributed Representation
https://github.com/nyu-dl/dl4mt-c2c
공식 코드Fully Character-Level Neural Machine Translation without Explicit Segmentation
https://github.com/nyu-dl/dl4mt-cdec
공식 코드Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder
https://github.com/nyu-dl/dl4mt-nonauto
공식 코드Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement
https://github.com/nyu-dl/dl4mt-seqgen
공식 코드A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models
https://github.com/nyu-dl/dl4mt-simul-trans
공식 코드Learning to Translate in Real-time with Neural Machine Translation
https://github.com/oaqa/FlexNeuART
공식 코드https://github.com/oasisresearchlab/crossdisciplinary-embeddings
공식 코드Words as Bridges: Exploring Computational Support for Cross-Disciplinary Translation Work
https://github.com/octavian-ganea/equidock_public
공식 코드Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
https://github.com/ofirpress/UsingTheOutputEmbedding
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.