https://github.com/cfedermann/Appraise
공식 코드Achieving Human Parity on Automatic Chinese to English News Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Achieving Human Parity on Automatic Chinese to English News Translation
Zero-Shot Information Extraction as a Unified Text-to-Triple Translation
Towards Offensive Language Identification for Tamil Code-Mixed YouTube Comments and Posts
Zero-Shot Language Transfer vs Iterative Back Translation for Unsupervised Machine Translation
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
Focus on the Target's Vocabulary: Masked Label Smoothing for Machine Translation
On the Off-Target Problem of Zero-Shot Multilingual Neural Machine Translation
Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision
Open-Domain Sign Language Translation Learned from Online Video
Dual-Alignment Pre-training for Cross-lingual Sentence Embedding
Diversifying Dialogue Generation with Non-Conversational Text
Textless Unit-to-Unit training for Many-to-Many Multilingual Speech-to-Speech Translation
Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search
DynE: Dynamic Ensemble Decoding for Multi-Document Summarization
Understood in Translation, Transformers for Domain Understanding
Supervised Symbolic Music Style Translation Using Synthetic Data
Multilingual Neural Machine Translation With Soft Decoupled Encoding
A Probabilistic Formulation of Unsupervised Text Style Transfer
Balancing Training for Multilingual Neural Machine Translation
Preserving Cultural Identity with Context-Aware Translation Through Multi-Agent AI Systems
How Programming Concepts and Neurons Are Shared in Code Language Models
Understanding In-Context Machine Translation for Low-Resource Languages: A Case Study on Manchu
1st Place Solution to MultiEarth 2023 Challenge on Multimodal SAR-to-EO Image Translation
PheMT: A Phenomenon-wise Dataset for Machine Translation Robustness on User-Generated Contents
Chat Translation Error Detection for Assisting Cross-lingual Communications
Translating Natural Language to Planning Goals with Large-Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.