1 citations · 2 across the 4 of their papers we have counts for
4 papers
CBSiMT: Mitigating Hallucination in Simultaneous Machine Translation with Weighted Prefix-to-Prefix Training
Mengge Liu, Wen Zhang, Xiang Li +5
Simultaneous machine translation (SiMT) is a challenging task that requires starting translation before the full source sentence is available. Prefix-to-prefix framework is often a…
Exploring Better Text Image Translation with Multimodal Codebook
Zhibin Lan, Jiawei Yu, Xiang Li +5
Text image translation (TIT) aims to translate the source texts embedded in the image to target translations, which has a wide range of applications and thus has important research…
Rethinking the Reasonability of the Test Set for Simultaneous Machine Translation
Mengge Liu, Wen Zhang, Xiang Li +4
Simultaneous machine translation (SimulMT) models start translation before the end of the source sentence, making the translation monotonically aligned with the source sentence. Ho…
BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation
Xiangyu Qin, Zhiyu Wu, Jinshi Cui +5
Previous works on emotion recognition in conversation (ERC) follow a two-step paradigm, which can be summarized as first producing context-independent features via fine-tuning pret…