nlp2ct Goto Github PK
Name: NLP2CT Lab, University of Macau
Type: Organization
Bio: Natural Language Processing & Portuguese - Chinese Machine Translation Laboratory
Location: Macau SAR, China
Name: NLP2CT Lab, University of Macau
Type: Organization
Bio: Natural Language Processing & Portuguese - Chinese Machine Translation Laboratory
Location: Macau SAR, China
Implementation of our paper in EMNLP 2022, focused on the relationship between parent and child in transfer learning for low-resource NMT
Improvements for Self-Attention, which is built based on THUMT
On the Copying Behaviors of Pre-Training for Neural Machine Translation (Findings of ACL 2021)
Difficulty-Aware Machine Translation Evaluation (ACL 2021)
Human-in-the-loop Machine Translation with Large Language Model
Leveraging Local and Global Patterns for Self-Attention Networks (ACL 2019)
A survey and reflection on the latest research breakthroughs in LLM-generated Text detection, including data, detectors, metrics, current issues and future directions.
Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation (AAAI 2021)
Code repository for the paper "Exploiting Multimodal Knowledge Graph for Multimodal Machine Translation"
MoNMT: Modularly Leveraging Monolingual and Bilingual Knowledge for Neural Machine Translation
A machine translation reading list maintained by Tsinghua Natural Language Processing Group
Norm-Based Curriculum Learning for Neural Machine Translation (ACL 2020)
Self-Paced Learning for Neural Machine Translation (EMNLP 2020)
TaU: Test-time Adaptation for Machine Translation Evaluation by Uncertainty Minimization
Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization
Uncertainty-Aware Curriculum Learning for Neural Machine Translation (ACL 2020)
Unsupervised Neural Dialect Translation with Commonality and Diversity Modeling (AAAI 2020)
Source code for the paper: Variance-Aware Machine Translation Test Sets (NeurIPS 2021 Datasets and Benchmarks Track)
This task is to study how well the word order information learned by different neural networks.
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