Uncertainty in natural language processing: Sources, quantification, and applications
As a main field of artificial intelligence, natural language processing (NLP) has achieved
remarkable success via deep neural networks. Plenty of NLP tasks have been addressed in …
remarkable success via deep neural networks. Plenty of NLP tasks have been addressed in …
Domain adaptation and multi-domain adaptation for neural machine translation: A survey
D Saunders - Journal of Artificial Intelligence Research, 2022 - jair.org
The development of deep learning techniques has allowed Neural Machine Translation
(NMT) models to become extremely powerful, given sufficient training data and training time …
(NMT) models to become extremely powerful, given sufficient training data and training time …
A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers
The rapid development of Large Language Models (LLMs) demonstrates remarkable
multilingual capabilities in natural language processing, attracting global attention in both …
multilingual capabilities in natural language processing, attracting global attention in both …
Unifying the convergences in multilingual neural machine translation
Although all-in-one-model multilingual neural machine translation (multilingual NMT) has
achieved remarkable progress, the convergence inconsistency in the joint training is …
achieved remarkable progress, the convergence inconsistency in the joint training is …
Towards higher pareto frontier in multilingual machine translation
Multilingual neural machine translation has witnessed remarkable progress in recent years.
However, the long-tailed distribution of multilingual corpora poses a challenge of Pareto …
However, the long-tailed distribution of multilingual corpora poses a challenge of Pareto …
Dlut-nlp machine translation systems for wmt24 low-resource indic language translation
DLUT-NLP Machine Translation Systems for WMT24 Low-Resource Indic Language Translation
Page 1 Proceedings of the Ninth Conference on Machine Translation, pages 742–746 November …
Page 1 Proceedings of the Ninth Conference on Machine Translation, pages 742–746 November …
Modeling Both Intra-and Inter-Modality Uncertainty for Multimodal Fake News Detection
Multimodal fake news detection has obtained increasing attention recently. Existing works
generally encode multimodal contents into a deterministic point in semantic subspaces, and …
generally encode multimodal contents into a deterministic point in semantic subspaces, and …
Importance-Aware Data Augmentation for Document-Level Neural Machine Translation
Document-level neural machine translation (DocNMT) aims to generate translations that are
both coherent and cohesive, in contrast to its sentence-level counterpart. However, due to its …
both coherent and cohesive, in contrast to its sentence-level counterpart. However, due to its …
Mixture-of-Skills: Learning to Optimize Data Usage for Fine-Tuning Large Language Models
Large language models (LLMs) are typically fine-tuned on diverse and extensive datasets
sourced from various origins to develop a comprehensive range of skills, such as writing …
sourced from various origins to develop a comprehensive range of skills, such as writing …
Optimizing the Training Schedule of Multilingual NMT using Reinforcement Learning
Multilingual NMT is a viable solution for translating low-resource languages (LRLs) when
data from high-resource languages (HRLs) from the same language family is available …
data from high-resource languages (HRLs) from the same language family is available …