https://github.com/boun-tabi/squad-tr
공식 코드Building Efficient and Effective OpenQA Systems for Low-Resource Languages
Papers with Code 아카이브
Machine Translation
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Machine translation is the task of translating a sentence in a source language to a different target language.
Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.
One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.
<span style="color:grey; opacity: 0.6">( Image credit: Google seq2seq )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bozheng-hit/xTune
공식 코드https://github.com/brendenlake/SCAN
공식 코드https://github.com/briviosimone/sae_eys
공식 코드Deep Symmetric Autoencoders from the Eckart-Young-Schmidt Perspective
https://github.com/bruceyg/dpo-mbr
공식 코드Direct Preference Optimization for Neural Machine Translation with Minimum Bayes Risk Decoding
https://github.com/bsavoldi/post-edit_guidelines
공식 코드https://github.com/burcgokden/Power-Law-Graph-Transformer
공식 코드Power Law Graph Transformer for Machine Translation and Representation Learning
https://github.com/bytedance/lightseq
공식 코드LightSeq: A High Performance Inference Library for Transformers
https://github.com/bytedance/neurst
공식 코드Towards Making the Most of BERT in Neural Machine Translation
https://github.com/bytedance/neurst/tree/master/examples/ctnmt
공식 코드Towards Making the Most of BERT in Neural Machine Translation
https://github.com/bzhangGo/ATR
공식 코드Simplifying Neural Machine Translation with Addition-Subtraction Twin-Gated Recurrent Networks
https://github.com/bzhangGo/sltunet
공식 코드SLTUNET: A Simple Unified Model for Sign Language Translation
https://github.com/bzhangGo/zero
공식 코드Simplifying Neural Machine Translation with Addition-Subtraction Twin-Gated Recurrent Networks
https://github.com/bzhangXMU/transformer-aan
공식 코드Accelerating Neural Transformer via an Average Attention Network
https://github.com/cair/tmu
공식 코드Tsetlin Machine Embedding: Representing Words Using Logical Expressions
https://github.com/calvinchengyx/cross-lan-mft-measure
공식 코드https://github.com/cambridgeltl/BLICEr
공식 코드Improving Bilingual Lexicon Induction with Cross-Encoder Reranking
https://github.com/cambridgeltl/ECNMT
공식 코드Emergent Communication Pretraining for Few-Shot Machine Translation
https://github.com/cambridgeltl/contrastivebli
공식 코드Improving Word Translation via Two-Stage Contrastive Learning
https://github.com/cambridgeltl/prompt4bli
공식 코드https://github.com/cambridgeltl/sail-bli
공식 코드Self-Augmented In-Context Learning for Unsupervised Word Translation
https://github.com/carhaas/nematus
공식 코드Learning Neural Sequence-to-Sequence Models from Weak Feedback with Bipolar Ramp Loss
https://github.com/carolscarton/iwslt2019
공식 코드https://github.com/castorini/duobert
공식 코드An Optimal Algorithm for Finding Champions in Tournament Graphs
https://github.com/catalystforyou/retro-bleu
공식 코드https://github.com/cbaziotis/fairseq
공식 코드https://github.com/cbaziotis/fairseq/tree/hyperadapters/examples/adapters
공식 코드https://github.com/cbaziotis/lm-prior-for-nmt
공식 코드Language Model Prior for Low-Resource Neural Machine Translation
https://github.com/cbaziotis/nmt-pretraining-objectives
공식 코드Exploring Unsupervised Pretraining Objectives for Machine Translation
https://github.com/cdli-gh/Semi-Supervised-NMT-for-Sumerian-English
공식 코드How Low is Too Low? A Computational Perspective on Extremely Low-Resource Languages
https://github.com/cdli-gh/Sumerian-Translation-Pipeline
공식 코드How Low is Too Low? A Computational Perspective on Extremely Low-Resource Languages
https://github.com/ceferisbarov/TUMLU
공식 코드TUMLU: A Unified and Native Language Understanding Benchmark for Turkic Languages
https://github.com/cepin19/semeval2020_task4
공식 코드https://github.com/cfedermann/Appraise
공식 코드Achieving Human Parity on Automatic Chinese to English News Translation
https://github.com/chaarangan/odl-tamil-sn
공식 코드Towards Offensive Language Identification for Tamil Code-Mixed YouTube Comments and Posts
https://github.com/chaitanyamalaviya/lang-reps
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.