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20152022
most citedBridging the Modality Gap for Speech-to-Text Translation

40 citations · 170 across the 24 of their papers we have counts for

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27 papers · 1 filter

cs.CL20223 cited

Life-long Learning for Multilingual Neural Machine Translation with Knowledge Distillation

Yang Zhao, Junnan Zhu, Lu Xiang +4

A common scenario of Multilingual Neural Machine Translation (MNMT) is that each translation task arrives in a sequential manner, and the training data of previous tasks is unavail…

cs.CL20221 cited

Learning Confidence for Transformer-based Neural Machine Translation

Yu Lu, Jiali Zeng, Jiajun Zhang +2

Confidence estimation aims to quantify the confidence of the model prediction, providing an expectation of success. A well-calibrated confidence estimate enables accurate failure p…

cs.CL20223 cited

Instance-aware Prompt Learning for Language Understanding and Generation

Feihu Jin, Jinliang Lu, Jiajun Zhang +1

Recently, prompt learning has become a new paradigm to utilize pre-trained language models (PLMs) and achieves promising results in downstream tasks with a negligible increase of p…

cs.CL202040 cited

Bridging the Modality Gap for Speech-to-Text Translation

Yuchen Liu, Junnan Zhu, Jiajun Zhang +1

End-to-end speech translation aims to translate speech in one language into text in another language via an end-to-end way. Most existing methods employ an encoder-decoder structur…

cs.CL2020

Dynamic Context Selection for Document-level Neural Machine Translation via Reinforcement Learning

Xiaomian Kang, Yang Zhao, Jiajun Zhang +1

Document-level neural machine translation has yielded attractive improvements. However, majority of existing methods roughly use all context sentences in a fixed scope. They neglec…

cs.CL202010 cited

Neural Machine Translation: Challenges, Progress and Future

Jiajun Zhang, Chengqing Zong

Machine translation (MT) is a technique that leverages computers to translate human languages automatically. Nowadays, neural machine translation (NMT) which models direct mapping…