Papers with Code 아카이브
Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 4
- 보존된 평가 기록
- 5
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/cyclomon/unsb
공식 코드Unpaired Image-to-Image Translation via Neural Schrödinger Bridge
https://github.com/cyjdswx/cones
공식 코드CoNeS: Conditional neural fields with shift modulation for multi-sequence MRI translation
https://github.com/cyq373/ZUNIT
공식 코드https://github.com/d-ataman/Char-NMT
공식 코드On the Importance of Word Boundaries in Character-level Neural Machine Translation
https://github.com/d-ataman/lmm
공식 코드A Latent Morphology Model for Open-Vocabulary Neural Machine Translation
https://github.com/d-keqi/mlta
공식 코드https://github.com/dahiyaaneesh/peclr
공식 코드https://github.com/daijifeng001/r-fcn
공식 코드R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/dalab/pboh-entity-linking
공식 코드https://github.com/dallascard/NLP-power-analysis
공식 코드https://github.com/dan11003/CFEAR_Radarodometry
공식 코드CFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar Odometry
https://github.com/danielajisafe/ASR-Nigeria-Pidgin
공식 코드Towards End-to-End Training of Automatic Speech Recognition for Nigerian Pidgin
https://github.com/danielholanda/LeFlow
공식 코드LeFlow: Enabling Flexible FPGA High-Level Synthesis of Tensorflow Deep Neural Networks
https://github.com/danielsc4/steering-for-personalization
공식 코드Steering Large Language Models for Machine Translation Personalization
https://github.com/danifg/disco-seq2seq-parser
공식 코드https://github.com/daniilidis-group/polar-transformer-networks
공식 코드https://github.com/dannigt/NMTGMinor.lowLatency
공식 코드Low-Latency Sequence-to-Sequence Speech Recognition and Translation by Partial Hypothesis Selection
https://github.com/dannigt/attribute-controller-transfer
공식 코드How Transferable are Attribute Controllers on Pretrained Multilingual Translation Models?
https://github.com/dannigt/fairseq/tree/master/examples/quant
공식 코드Learning an Artificial Language for Knowledge-Sharing in Multilingual Translation
https://github.com/dannigt/kit-iwslt2023-multilingual
공식 코드https://github.com/danoneata/strim
공식 코드https://github.com/danwley/globe-ce
공식 코드GLOBE-CE: A Translation-Based Approach for Global Counterfactual Explanations
https://github.com/dapascual/DirectedBeamSearch
공식 코드Directed Beam Search: Plug-and-Play Lexically Constrained Language Generation
https://github.com/darija-open-dataset/dataset
공식 코드https://github.com/datquocnguyen/STransE
공식 코드STransE: a novel embedding model of entities and relationships in knowledge bases
https://github.com/davidstap/multilingual-knn-mt
공식 코드https://github.com/dayeonki/mt_feedback
공식 코드Guiding Large Language Models to Post-Edit Machine Translation with Error Annotations
https://github.com/dayeonki/mt_quality_feedback
공식 코드https://github.com/dayeonki/rewrite_mt
공식 코드Automatic Input Rewriting Improves Translation with Large Language Models
https://github.com/dbash/pix2pix_cyclegan_guess_noise
공식 코드https://github.com/dbash/umi2i_correctness
공식 코드Evaluation of Correctness in Unsupervised Many-to-Many Image Translation
https://github.com/dbolya/yolact
공식 코드https://github.com/dcsaunders/nmt-gender-rerank
공식 코드First the worst: Finding better gender translations during beam search
https://github.com/dcu-nlg/dcu-nlg-pbn
공식 코드https://github.com/ddghjikle/out-of-sample-restoration
공식 코드Generalizing to Out-of-Sample Degradations via Model Reprogramming
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.