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NMT
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Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT
Enhancing Meme Token Market Transparency: A Multi-Dimensional Entity-Linked Address Analysis for Liquidity Risk Evaluation
In-Domain African Languages Translation Using LLMs and Multi-armed Bandits
THOR-MoE: Hierarchical Task-Guided and Context-Responsive Routing for Neural Machine Translation
Combining the Best of Both Worlds: A Method for Hybrid NMT and LLM Translation
Are We Paying Attention to Her? Investigating Gender Disambiguation and Attention in Machine Translation
TopicVD: A Topic-Based Dataset of Video-Guided Multimodal Machine Translation for Documentaries
Do Not Change Me: On Transferring Entities Without Modification in Neural Machine Translation -- a Multilingual Perspective
Data Augmentation With Back translation for Low Resource languages: A case of English and Luganda
AI agents may be worth the hype but not the resources (yet): An initial exploration of machine translation quality and costs in three language pairs in the legal and news domains
Calibrating Translation Decoding with Quality Estimation on LLMs
Is LLM the Silver Bullet to Low-Resource Languages Machine Translation?
Beyond Vanilla Fine-Tuning: Leveraging Multistage, Multilingual, and Domain-Specific Methods for Low-Resource Machine Translation
Contextual Cues in Machine Translation: Investigating the Potential of Multi-Source Input Strategies in LLMs and NMT Systems
Beyond Decoder-only: Large Language Models Can be Good Encoders for Machine Translation
MultiSlav: Using Cross-Lingual Knowledge Transfer to Combat the Curse of Multilinguality
Quality-Aware Decoding: Unifying Quality Estimation and Decoding
Evaluation of NMT-Assisted Grammar Transfer for a Multi-Language Configurable Data-to-Text System
Faster Machine Translation Ensembling with Reinforcement Learning and Competitive Correction
Proverbs Run in Pairs: Evaluating Proverb Translation Capability of Large Language Model
Extend Adversarial Policy Against Neural Machine Translation via Unknown Token
Bridging Dialects: Translating Standard Bangla to Regional Variants Using Neural Models
AFRIDOC-MT: Document-level MT Corpus for African Languages
Quality Estimation based Feedback Training for Improving Pronoun Translation
Sinhala Transliteration: A Comparative Analysis Between Rule-based and Seq2Seq Approaches
Enhancing Entertainment Translation for Indian Languages using Adaptive Context, Style and LLMs
Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation
An Analysis on Automated Metrics for Evaluating Japanese-English Chat Translation
Advancing Explainability in Neural Machine Translation: Analytical Metrics for Attention and Alignment Consistency
Domain adapted machine translation: What does catastrophic forgetting forget and why?
Reconsidering SMT Over NMT for Closely Related Languages: A Case Study of Persian-Hindi Pair
Understanding and Analyzing Model Robustness and Knowledge-Transfer in Multilingual Neural Machine Translation using TX-Ray
ParMod: A Parallel and Modular Framework for Learning Non-Markovian Tasks
MT-LENS: An all-in-one Toolkit for Better Machine Translation Evaluation
A Comparative Study of LLMs, NMT Models, and Their Combination in Persian-English Idiom Translation
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