nlp2ct Goto Github PK

awesome-speech-translation

consisttl

Implementation of our paper in EMNLP 2022, focused on the relationship between parent and child in transfer learning for low-resource NMT

context-aware-san

Improvements for Self-Attention, which is built based on THUMT

copyingpenalty

On the Copying Behaviors of Pre-Training for Neural Machine Translation (Findings of ACL 2021)

difficulty-aware-mt-evaluation

Difficulty-Aware Machine Translation Evaluation (ACL 2021)

e-att

hil-mt

Human-in-the-loop Machine Translation with Large Language Model

knn-tl

leveraging

Leveraging Local and Global Patterns for Self-Attention Networks (ACL 2019)

llm-generated-text-detection

A survey and reflection on the latest research breakthroughs in LLM-generated Text detection, including data, detectors, metrics, current issues and future directions.

master-thesis-stuff

meta-curriculum

Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation (AAAI 2021)

mmkg_mmt

Code repository for the paper "Exploiting Multimodal Knowledge Graph for Multimodal Machine Translation"

monmt

MoNMT: Modularly Leveraging Monolingual and Bilingual Knowledge for Neural Machine Translation

mt-reading-list

A machine translation reading list maintained by Tsinghua Natural Language Processing Group

multimodalgec

mv-attn

norm-nmt

Norm-Based Curriculum Learning for Neural Machine Translation (ACL 2020)

prettyalign

spl_for_nmt

Self-Paced Learning for Neural Machine Translation (EMNLP 2020)

tau

TaU: Test-time Adaptation for Machine Translation Evaluation by Uncertainty Minimization

temposum

Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization

transgec

ua-cl-nmt

Uncertainty-Aware Curriculum Learning for Neural Machine Translation (ACL 2020)

unite

unsupervised_dialect_translation

Unsupervised Neural Dialect Translation with Commonality and Diversity Modeling (AAAI 2020)

variance-aware-mt-test-sets

Source code for the paper: Variance-Aware Machine Translation Test Sets (NeurIPS 2021 Datasets and Benchmarks Track)

wrd

This task is to study how well the word order information learned by different neural networks.