256 citations · 354 across the 17 of their papers we have counts for
15 papers · 1 filter
Secrets of RLHF in Large Language Models Part I: PPO
Rui Zheng, Shihan Dou, Songyang Gao +24
Large language models (LLMs) have formulated a blueprint for the advancement of artificial general intelligence. Its primary objective is to function as a human-centric (helpful, h…
Towards Reliable Neural Machine Translation with Consistency-Aware Meta-Learning
Rongxiang Weng, Qiang Wang, Wensen Cheng +2
Neural machine translation (NMT) has achieved remarkable success in producing high-quality translations. However, current NMT systems suffer from a lack of reliability, as their ou…
Learning Decoupled Retrieval Representation for Nearest Neighbour Neural Machine Translation
Qiang Wang, Rongxiang Weng, Ming Chen
K-Nearest Neighbor Neural Machine Translation (kNN-MT) successfully incorporates external corpus by retrieving word-level representations at test time. Generally, kNN-MT borrows th…
Learning to Generalize to More: Continuous Semantic Augmentation for Neural Machine Translation
Xiangpeng Wei, Heng Yu, Yue Hu +4
The principal task in supervised neural machine translation (NMT) is to learn to generate target sentences conditioned on the source inputs from a set of parallel sentence pairs, a…
Uncertainty-Aware Semantic Augmentation for Neural Machine Translation
Xiangpeng Wei, Heng Yu, Yue Hu +3
As a sequence-to-sequence generation task, neural machine translation (NMT) naturally contains intrinsic uncertainty, where a single sentence in one language has multiple valid cou…
On Learning Universal Representations Across Languages
Xiangpeng Wei, Rongxiang Weng, Yue Hu +3
Recent studies have demonstrated the overwhelming advantage of cross-lingual pre-trained models (PTMs), such as multilingual BERT and XLM, on cross-lingual NLP tasks. However, exis…
Multiscale Collaborative Deep Models for Neural Machine Translation
Xiangpeng Wei, Heng Yu, Yue Hu +3
Recent evidence reveals that Neural Machine Translation (NMT) models with deeper neural networks can be more effective but are difficult to train. In this paper, we present a Multi…
AR: Auto-Repair the Synthetic Data for Neural Machine Translation
Shanbo Cheng, Shaohui Kuang, Rongxiang Weng +3
Compared with only using limited authentic parallel data as training corpus, many studies have proved that incorporating synthetic parallel data, which generated by back translatio…
GRET: Global Representation Enhanced Transformer
Rongxiang Weng, Haoran Wei, Shujian Huang +4
Transformer, based on the encoder-decoder framework, has achieved state-of-the-art performance on several natural language generation tasks. The encoder maps the words in the input…
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation
Rongxiang Weng, Heng Yu, Shujian Huang +2
Pre-training and fine-tuning have achieved great success in the natural language process field. The standard paradigm of exploiting them includes two steps: first, pre-training a m…
Improving Neural Machine Translation with Pre-trained Representation
Rongxiang Weng, Heng Yu, Shujian Huang +2
Monolingual data has been demonstrated to be helpful in improving the translation quality of neural machine translation (NMT). The current methods stay at the usage of word-level k…
Correct-and-Memorize: Learning to Translate from Interactive Revisions
Rongxiang Weng, Hao Zhou, Shujian Huang +3
State-of-the-art machine translation models are still not on par with human translators. Previous work takes human interactions into the neural machine translation process to obtai…
Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
Peng Wu, Shujian Huang, Rongxiang Weng +4
Relation detection is a core step in many natural language process applications including knowledge base question answering. Previous efforts show that single-fact questions could…
Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation
Zaixiang Zheng, Shujian Huang, Zewei Sun +3
Previous studies show that incorporating external information could improve the translation quality of Neural Machine Translation (NMT) systems. However, there are inevitably noise…
Neural Machine Translation with Word Predictions
Rongxiang Weng, Shujian Huang, Zaixiang Zheng +2
In the encoder-decoder architecture for neural machine translation (NMT), the hidden states of the recurrent structures in the encoder and decoder carry the crucial information abo…