https://github.com/xu1998hz/sescore2
공식 코드SESCORE2: Learning Text Generation Evaluation via Synthesizing Realistic Mistakes
Papers with Code 아카이브
Translation
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/xuchennlp/s2t
공식 코드https://github.com/xuekt98/bbdm
공식 코드BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models
https://github.com/xuuhuang/imtlab
공식 코드https://github.com/xuuhuang/lost_in_the_src
공식 코드Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine Translation
https://github.com/xuwangyin/at-ebms
공식 코드https://github.com/xuyuzhuang11/stylemt
공식 코드Pluggable Neural Machine Translation Models via Memory-augmented Adapters
https://github.com/xwgeng/SSAN
공식 코드How Does Selective Mechanism Improve Self-Attention Networks?
https://github.com/xycforgithub/MultiTask-MRC
공식 코드Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension
https://github.com/xydaytoy/BMI-NMT
공식 코드Bilingual Mutual Information Based Adaptive Training for Neural Machine Translation
https://github.com/xypan0/G-DIG
공식 코드https://github.com/yafuly/CoGnition
공식 코드On Compositional Generalization of Neural Machine Translation
https://github.com/yafuly/mgmo-nat
공식 코드Multi-Granularity Optimization for Non-Autoregressive Translation
https://github.com/yahoo/YaraParser
공식 코드https://github.com/yajun-zhou/linguae-naturalis-principia-mathematica
공식 코드https://github.com/yakazimir/Code-Datasets
공식 코드https://github.com/yale-lily/ascle
공식 코드Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation
https://github.com/yale-lily/folio
공식 코드https://github.com/yale-lily/medgen
공식 코드Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation
https://github.com/yandex-research/msr
공식 코드https://github.com/yandex-research/navigan
공식 코드Navigating the GAN Parameter Space for Semantic Image Editing
https://github.com/yangbang18/zeronlg
공식 코드https://github.com/yangheng95/DaNuoYi
공식 코드Evolutionary Multi-Task Injection Testing on Web Application Firewalls
https://github.com/yangkevin2/emnlp2020-stream-beam-mt
공식 코드https://github.com/yangkevin2/naacl-2021-fudge-controlled-generation
공식 코드FUDGE: Controlled Text Generation With Future Discriminators
https://github.com/yangorwell/NGPlus
공식 코드NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning
https://github.com/yangyiben/G-DAUG-c-Generative-Data-Augmentation-for-Commonsense-Reasoning
공식 코드https://github.com/yanyao-shen/fairseq
공식 코드https://github.com/yaohungt/TransformerDissection
공식 코드Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of Kernel
https://github.com/yaoli/chest_xray_14
공식 코드Learning to diagnose from scratch by exploiting dependencies among labels
https://github.com/yaoming95/23triplet
공식 코드Beyond Triplet: Leveraging the Most Data for Multimodal Machine Translation
https://github.com/yaoming95/ciat
공식 코드Counter-Interference Adapter for Multilingual Machine Translation
https://github.com/yaxingwang/DeepI2I
공식 코드DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs
https://github.com/yaxingwang/Mix-and-match-networks
공식 코드Mix and match networks: encoder-decoder alignment for zero-pair image translation
https://github.com/yaxingwang/SDIT
공식 코드https://github.com/yaxingwang/SEMIT
공식 코드Semi-supervised Learning for Few-shot Image-to-Image Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.