Automatic Post-Editing
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Automatic post-editing (APE) is used to correct errors in the translation made by the machine translation systems.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/THUNLP-MT/THUMT
공식 코드https://github.com/THUNLP-MT/TRICE
공식 코드Transfer Learning for Sequence Generation: from Single-source to Multi-source
https://github.com/antoniogois/keystrokes_ape
공식 코드Learning Non-Monotonic Automatic Post-Editing of Translations from Human Orderings
https://github.com/chrishokamp/constrained_decoding
공식 코드https://github.com/chrishokamp/dynamic-transformer-ensembles
공식 코드DynE: Dynamic Ensemble Decoding for Multi-Document Summarization
https://github.com/coldmist-lu/mqm_ape
공식 코드https://github.com/deep-spin/OpenNMT-APE
공식 코드A Simple and Effective Approach to Automatic Post-Editing with Transfer Learning
https://github.com/google-research/google-research/tree/master/felix
공식 코드https://github.com/ijauregiCMCRC/Shared_Attention_for_APE
공식 코드A Shared Attention Mechanism for Interpretation of Neural Automatic Post-Editing Systems
https://github.com/lena-voita/good-translation-wrong-in-context
공식 코드Context-Aware Monolingual Repair for Neural Machine Translation
https://github.com/lilt/tec
공식 코드https://github.com/pytorch/fairseq
공식 코드https://github.com/shamilcm/pedra
공식 코드https://github.com/sheffieldnlp/mlqe-pe
공식 코드MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
https://github.com/tienthanhdhcn/VnAPE
공식 코드https://github.com/ufal/neuralmonkey
공식 코드Attention Strategies for Multi-Source Sequence-to-Sequence Learning
https://github.com/zerocstaker/constrained_ape
공식 코드Incorporating Terminology Constraints in Automatic Post-Editing
https://github.com/ictnlp/Seq-NAT
https://github.com/maxwell1447/fairseq
https://github.com/osu-nlp-group/llm-cn-eval
https://github.com/phanxuanphucnd/Felix
https://github.com/reichang182/variable-length-piano-infilling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.