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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/tsuruoka-lab/BSD

공식 코드

Designing the Business Conversation Corpus

https://github.com/tuanh23/multimodalst

공식 코드

Tackling data scarcity in speech translation using zero-shot multilingual machine translation techniques

https://github.com/tuanh23/perturbation-basedqe

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Perturbation-based QE: An Explainable, Unsupervised Word-level Quality Estimation Method for Blackbox Machine Translation

https://github.com/tueimage/se2cnn

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Roto-Translation Covariant Convolutional Networks for Medical Image Analysis

https://github.com/tuffr5/CAR-GAN

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Cascade Attention Guided Residue Learning GAN for Cross-Modal Translation

https://github.com/tuhinjubcse/poetrytranslationemnlp2021

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Don't Go Far Off: An Empirical Study on Neural Poetry Translation

https://github.com/turkunlp/paraphrase-span-detection

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Semantic Search as Extractive Paraphrase Span Detection

https://github.com/tushar117/Transformer-Models-for-Text-Coherence-Assessment

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Transformer Models for Text Coherence Assessment

https://github.com/tuzhaopeng/LC-NMT

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Exploiting Cross-Sentence Context for Neural Machine Translation

https://github.com/tuzhaopeng/NMT-Coverage

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Modeling Coverage for Neural Machine Translation

https://github.com/tuzhaopeng/nmt

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Context Gates for Neural Machine Translation

https://github.com/twadada/multilingual-nlm

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Learning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora

https://github.com/txie-93/cdvae

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Crystal Diffusion Variational Autoencoder for Periodic Material Generation

https://github.com/tychovdo/RevGAN

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Reversible GANs for Memory-efficient Image-to-Image Translation

https://github.com/tyliupku/Arbitrary-Order-Infnet

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An Exploration of Arbitrary-Order Sequence Labeling via Energy-Based Inference Networks

https://github.com/tzshi/squall

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On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL Queries

https://github.com/ualsg/ganmapper

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GANmapper: geographical data translation

https://github.com/ubc-nlp/mos

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Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts

https://github.com/ubc-nlp/nilechat

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NileChat: Towards Linguistically Diverse and Culturally Aware LLMs for Local Communities

https://github.com/ubc-nlp/turjuman

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TURJUMAN: A Public Toolkit for Neural Arabic Machine Translation

https://github.com/uber-research/coordconv

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An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

https://github.com/uclanlp/paraamr

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ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation

https://github.com/uds-lsv/3st

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Exploiting Social Media Content for Self-Supervised Style Transfer

https://github.com/uds-lsv/author-profiling-prevention-bt

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Preventing Author Profiling through Zero-Shot Multilingual Back-Translation

https://github.com/ufal/MT-metrics-in-SimST

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MT Metrics Correlate with Human Ratings of Simultaneous Speech Translation

https://github.com/ufal/augpt

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AuGPT: Auxiliary Tasks and Data Augmentation for End-To-End Dialogue with Pre-Trained Language Models

https://github.com/ufal/eyetracked-multi-modal-translation

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EMMT: A simultaneous eye-tracking, 4-electrode EEG and audio corpus for multi-modal reading and translation scenarios

https://github.com/ufal/kazitext

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Understanding Model Robustness to User-generated Noisy Texts

https://github.com/ufal/legros

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Lexically Grounded Subword Segmentation

https://github.com/ufal/legros-paper

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Lexically Grounded Subword Segmentation

https://github.com/ufal/low-resource-gec-wnut2019

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Grammatical Error Correction in Low-Resource Scenarios

https://github.com/ufal/neuralmonkey

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Attention Strategies for Multi-Source Sequence-to-Sequence Learning

https://github.com/ufal/optimal-reference-translations

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Evaluating Optimal Reference Translations

https://github.com/ufal/whisper_streaming

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Turning Whisper into Real-Time Transcription System

https://github.com/uhh-lt/bert-sense

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Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings

https://github.com/ulmewennberg/tisa

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The Case for Translation-Invariant Self-Attention in Transformer-Based Language Models

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.